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Courses Catalog

Front End
HTML
HTML Intro
How Works HTML
HTML Tools
HTML First Document
HTML Basic Structure
HTML Code in the HTML Browser
HTML Tags
HTML Tags and Attributes
HTML Common Tags: <div>, <span>, <h1>-<h6>, <p>, <br>, <hr>
HTML Lists
HTML Ordered Lists (<ol>, <li>)
HTML Unordered Lists (<ul>, <li>)
HTML Images in HTML: <img>
HTML Insert Images <img>
Intro to Semantic Tags
HTML Semantic Tags
HTML Meta Tags and SEO
HTML Character Encoding and the <meta> Tag
HTML Links
html Creating Links <a>
HTML Link Attributes: href and target
HTML Internal and External Links
HTML Email Links in HTML (mailto:)
HTML Tables
HTML Creating a Table (<table>, <tr>, <td>, <th>)
HTML Table Attributes: border, cellpadding, cellspacing
HTML Creating Table Headers and Merged Cells
HTML Forms
HTML Form Structure (<form>)
HTML Form Fields (<input type="text">, password, submit)
HTML Buttons (<button>, input type="button")
HTML Select Fields (<select>, <option>)
HTML Checkboxes and Radios (<input type="checkbox">, radio)
HTML Multimedia Elements
HTML Adding Video: <video>, attributes controls, autoplay, loop
HTML Adding Audio: <audio>, attributes controls, autoplay, loop
HTML Using <iframe> in HTML
HTML Semantic Tags: <header>, <nav>, <section>, <article>, <aside>, <footer>
HTML Titles and Favicons (<title>, <link>)
HTML Comments
HTML Links and Navigation
HTML Navigation Menus
HTML5 and Browser API
HTML Geolocation API
Local Storage API (localStorage)
HTML Validation
Using HTML Validators
HTML Common Errors and How to Fix Them
HTML Mastery Quiz
CSS
Introduction to CSS
CSS Syntax
CSS Incorporation
CSS Basic Selectors
CSS Colors
CSS Fonts and Text
CSS Text Alignment
CSS Background Properties
CSS Gradients
CSS Background Image
Box Model
CSS Width and Height
CSS Margin and Padding
CSS Borders
CSS Box Sizing
CSS Overflow
CSS Display
CSS Positioning
CSS Z-Index
CSS Float
CSS Alignment
CSS Flexbox Intro
CSS Flexbox Container
CSS Flex Direction
CSS Justify Content
CSS Align Items
CSS Flex Wrap
CSS Flexbox Items
CSS Display Grid
CSS Grid Columns
CSS Grid Rows
CSS Grid Gap
CSS Grid Area
CSS Relative Units
CSS Media Queries
CSS Responsive Design
CSS Frameworks
CSS Transitions and Animations
CSS Keyframes
CSS Advanced Effects
CSS Foundations Quiz
JavaScript
JavaScript Introduction
JavaScript Basic Syntax
JavaScript Operators
JavaScript Comments
JavaScript Control Structure
JavaScript Conditionals
JavaScript Loops
JavaScript Functions
Declaration, anonymous and arrow functions
JavaScript Return Arguments and Parameters
JavaScript Scope
JavaScript Arrays and Objects
JavaScript Objects
JavaScript Common Methods (push, map, filter)
JavaScript Array Loops (for, forEach)
JavaScript DOM (Document Object Model)
JavaScript Manipulatio (getElementById, innerHTML)
JavaScript Style Modification
JavaScript Events addEventListener
JavaScript BOM (Browser Object Model)
Objetos: window, document, location, history
JavaScript Windows Manipulation and Redirects
JavaScript Advance Functions
Javacript HOC, Closures, and recursivity
JavaScript Callback Functions
JavaScript Object-Oriented Programming(OOP)
Classes, Inheritance, Constructors
JavaScript Prototypes and Inherance
JavaScript Async Function and Promises
Introduction to Asynchronous Programming
JavaScript Promises (then, catch) and use of async/await
JavaScript Events
JavaScript Common Events: mouse, keyboard and forms
JavaScript Propagation and events delegation
JavaScript Dates and Time
JavaScript Dates and Methods
JavaScript setTimeout y setInterval
JavaScript JSON, Manipulation Data and API
JavaScript JSON Works (JSON.stringify, JSON.parse)
JavaScript Fetch API for HTTP request (GET, POST)
JavaScript Storage
localStorage, sessionStorage, y cookies
JavaScript Modules
JavaScript Export and import modules (export, import)
JavaScript Modular Code
JavaScript Errors and Debugging
JavaScript Errors (try, catch, throw)
JavaScript Debugging Tools
JavaScript Logic Quiz
React
React Introduction
React Components Intro
React Tools
React Introduction Jsx
React First Steps
React Structure
React Components, Props, State
React JSX
Difference Function vs Class
React Components
React Functional Components
React Props
React State with useState
React Class Components
React Re-use Components
React Communication Between Components
React JSX Advance
React Syntax JSX
React JSX Expressions
React inline and Class Styles
React Loops and Conditionals
React Fragments
React State Management
React State Intro
React Local State vs Global State
React useState
React Forms and state Management inputs
React Hooks
React useEffect
React useContext
React useRef
React useReducer
React Custom Hooks
React Events
Eventos common: onClick, onChange, onSubmit, etc.
Eventos sintéticos React
React PreventDefault
React Conditional Rendering and Lists
React Conditional Render
React map()
React key in List
React Render
React CSS Style
React inline and Class Styles
React CSS Modules
React Dynamic Style
React Style Libraries
React Router
React-router-dom
React Dynamic Routes
React Route, Switch, y Link
React URL
React useHistory
Redux Intro
Redux Install
React Store, Actions, Reducers
React Redux Hooks
React Forms
React APIs
React HttpAxios
React LazySuspense
React Condicional vs Lazy vs Suspense
React React.memo y useMemo
Angular
Angular Introduction
Angular Architecture
Create Angular Project
👑 PRO
Angular Components
Template, style and logic
Data Binding Angular
Event Binding Angular
Directives Intro
Structural Directives
Attribute Directives
Custom Directives
Services and DI Intro
Angular Services
Angular Injectables
Singleton Services
Navigation and Routing Intro
Routes Configuration
Routing and Navigation
Dynamic Routes and Parameters
Child Routes & Lazy Loading
Angular Forms Intro
Template-Driven Forms
Reactive Forms & Validation
HTTP & API Consumption
HttpClient & Configuration
RESTful HTTP Requests
HTTP Error Handling
RxJS Introduction
Observables & Lifecycle
RxJS Operators Mastery
The Async Pipe
Angular Modules (NgModules)
Standalone Components
Advanced Dependency Injection
Component Lifecycle Mastery
Testing Foundations
Component Testing Mastery
Service & Logic Testing
Launch: Deploy & Optimize
Vue
What is Vue?
Setup & The App Instance
Reactivity: ref vs reactive
Computed Properties
Methods & Event Handling
Two-Way Binding (v-model)
Conditional Rendering
List Rendering
Lifecycle Hooks
Components & Props
Slots
Watchers
Provide / Inject
Composables
Vue Router Intro
Three
Introduction to WebGL & Three.js
Creating a Scene
Cameras & Perspectives
The WebGL Renderer
Geometries
Materials
Meshes & Transformations
Lighting
Shadows
Textures & Mapping
The Animation Loop
Orbit Controls
Particles & Sprites
Importing 3D Models
Raycaster & Interaction
Physics Integration
Custom Shaders
Build Apps with AI
Responsive and Accessible Interface Design
Forms and User Input Handling (Prompts)
API Requests and Middleware
Connecting with OpenAI and Hugging Face APIs
Real-time AI Content Rendering
Loading States and UX in AI Applications
Topic 3: Machine Learning in the Browser
TensorFlow.js Fundamentals
Introduction to Client-side Machine Learning
Advantages of Running ML in the Browser (Low Latency)
Using Pre-trained Models
Implementing ML Logic with JavaScript
Running Predictions without a Server
Building Data Pipelines in the Browser
AI Data Visualization
Testing and Debugging AI Functions
Topic 4: Deployment and Final Project (Capstone)
👑 PRO
Deployment Platforms: Vercel, Render and AWS
Production Configuration
Cost Optimization and API Usage
Performance Monitoring
Logging Model Calls
Ethical UX Design
Mitigating Bias in AI Responses
Capstone Project: Planning and Architecture
👑 PRO
Capstone Project: Development of Complete AI Web Application
👑 PRO
Capstone Project: Presentation and Functional Demo
👑 PRO
Artificial Intelligence
AI Foundations
01. AI Foundations
Introduction to Artificial Intelligence & History
AI vs. Machine Learning vs. Deep Learning
Python for Data Science (NumPy, Pandas Review)
Data Visualization (Matplotlib, Seaborn)
Setting up the Environment (Jupyter, Google Colab)
02. Data Processing
Exploratory Data Analysis (EDA)
Data Cleaning and Handling Missing Values
Feature Scaling and Normalization
Feature Encoding (One-Hot, Label Encoding)
Splitting Data (Train/Test/Validation Sets)
03. Supervised Learning
Introduction to Supervised Learning
Linear Regression (Simple & Multiple)
Logistic Regression
Decision Trees and Random Forests
Support Vector Machines (SVM)
Evaluation Metrics (RMSE, Accuracy, Precision, Recall, F1)
04. Unsupervised Learning
Introduction to Unsupervised Learning
K-Means Clustering
Hierarchical Clustering
Dimensionality Reduction (PCA)
Recommender Systems Basics
05. Neural Networks (Deep Learning)
Introduction to Artificial Neural Networks (ANN)
Perceptrons and Activation Functions (ReLU, Sigmoid)
Forward Propagation vs. Backpropagation
Loss Functions and Optimizers (Adam, SGD)
Handling Overfitting (Dropout, Regularization)
06. Computer Vision
Introduction to Convolutional Neural Networks (CNN)
Building CNNs with TensorFlow/Keras or PyTorch
Image Augmentation Techniques
Transfer Learning (VGG16, ResNet)
Object Detection Basics (YOLO intro)
07. Natural Language Processing (NLP)
Text Preprocessing (Tokenization, Stemming, Lemmatization)
Bag of Words & TF-IDF
Word Embeddings (Word2Vec, GloVe)
Recurrent Neural Networks (RNN) & LSTMs
Introduction to Transformers (Attention Mechanism)
08. Generative AI & LLMs
Introduction to Large Language Models (LLMs)
Prompt Engineering Strategies
Using OpenAI / Anthropic APIs
Retrieval-Augmented Generation (RAG) Basics
Image Generation (Diffusion Models Intro)
09. Deployment & Ethics
Saving and Loading Models (Pickle, Joblib)
Creating an API with FastAPI/Flask
Containerization (Docker Basics for AI)
AI Ethics: Bias, Fairness, and Explainability
Future Trends in AI
Automation
01. Automation Foundations
Introduction to Low-Code & No-Code Automation
Understanding APIs, Webhooks, and API Keys
Data Structures 101: JSON for Marketers
The Landscape: n8n vs. Make (Integromat) vs. Zapier
Setting up OpenAI API & Anthropic API
02. Getting Started with n8n
02. Getting Started with n8n
Installing n8n (Cloud vs. Self-Hosted/Docker)
The n8n Interface: Nodes, Connections, and Workflows
Understanding the Trigger Node
Core Nodes: Set, IF, Switch, and Merge
Your First Workflow: Form to Email/Slack Notification
03. AI Content Engines
Building an Idea-to-Article Generator
Integrating Search (SerpApi) for SEO-Driven AI Content
Automated WordPress Publishing via n8n
Image Generation Pipeline (Midjourney/DALL-E API)
Repurposing: Converting YouTube Transcripts to Blog Posts
04. Social Media Automation
Automated Social Listening & Sentiment Analysis
Content Distribution: Auto-posting to LinkedIn/X/Instagram
AI Comment Generator for Engagement
Dynamic Image Creation for Social (Bannerbear + AI)
05. Lead Gen & CRM Ops
Connecting Lead Forms (Typeform/Facebook) to CRMs (HubSpot)
👑 PRO
Automated Lead Enrichment (Clearbit/Apollo + AI Scraping)
AI Lead Scoring: Grading Leads based on Data
Personalized Cold Outreach Generation
06. Advanced n8n Logic
Working with Arrays and Loops (Item Lists)
The HTTP Request Node: Connecting to Any API
The Code Node: Basic JavaScript for Data Transformation
Error Handling and Retry Strategies
Webhooks: Receiving Real-time Data
07. Email & Support Automation
Auto-Categorizing Incoming Emails (Support vs. Sales)
AI Draft Replies for Customer Support (Human-in-the-loop)
Weekly Newsletter Compilation (RSS + AI Summarizer)
08. Building AI Agents
Introduction to LangChain in n8n
Creating a Chatbot with Memory
RAG Basics: Chatting with your own PDF/Notion Data
Web Scraping Agents (Puppeteer/ScrapingBee)
09. Operations & Scale
Database Syncing (Google Sheets / Airtable / PostgreSQL)
Document Parsing (PDF Invoice to Data)
Managing API Costs and Rate Limits
Security Best Practices for Automations
👑 PRO
MLOps & Model Deployment
Module 1: Foundations & Setup
Intro To Machine Learning Operations
The ML Lifecycle
Version Control For Data DVC
Intro To Docker For ML
Creating Dockerfiles For Models
Module 2: Core Architecture & Components
Docker Compose For ML Apps
Building Fast API For Models
REST vs g RPC For Model Serving
Intro To Tensor Flow Serving
Continuous Integration For ML
Module 3: Advanced Capabilities & Workflows
Git Hub Actions For ML Pipelines
Automated Model Testing
Model Drift And Data Drift
Monitoring With Prometheus Grafana
A B Testing For ML Models
Module 4: Practical Implementation & Capstones
Capstone End To End Deployment
Reinforcement Learning
Module 1: Foundations & Setup
Intro To Reinforcement Learning
Markov Decision Processes MDPs
Dynamic Programming Basics
Rewards And Return
Monte Carlo Methods
Module 2: Core Architecture & Components
Temporal Difference Learning TD
Q Learning Explained
Intro To Deep Q Networks DQN
Experience Replay And Target Networks
Policy Gradient Methods REINFORCE
Module 3: Advanced Capabilities & Workflows
Actor Critic Methods
Proximal Policy Optimization PPO
Soft Actor Critic SAC
Intro To Open AI Gym Gymnasium
Building Custom Environments
Module 4: Practical Implementation & Capstones
Multi Agent Reinforcement Learning
Capstone Train AI To Play A Game
AI Ethics, Safety & Alignment
Module 1: Foundations & Setup
Intro To AI Ethics
History Of AI Failures
The Alignment Problem
Understanding Algorithmic Bias
Measuring Fairness In Models
Module 2: Core Architecture & Components
Mitigating Bias Techniques
Intro To Explainable AI
LIME And SHAP Values
Data Privacy Laws GDPR
Federated Learning Basics
Module 3: Advanced Capabilities & Workflows
Interpreting Deep Learning Models
Adversarial Attacks On AI
AI Regulations EU AI Act
Corporate AI Guidelines
Future Of AGI And Society
Module 4: Practical Implementation & Capstones
Capstone Auditing An AI System
Audio & Speech Processing
Module 1: Foundations & Setup
Intro To Sound Waves
Digital Audio And Sampling
Working With Librosa
Spectrograms And Mel Scale
MFCCs Explained
Module 2: Core Architecture & Components
Zero Crossing Rate And Energy
Intro To Speech To Text
Hidden Markov Models HMM
Deep Learning For ASR Wav2Vec
Intro To Text To Speech
Module 3: Advanced Capabilities & Workflows
Vocoders And Spectrogram Inversion
Modern TTS Tacotron
Environmental Sound Recognition
Music Genre Classification
Voice Activity Detection VAD
Module 4: Practical Implementation & Capstones
Capstone Voice Command Assistant
Time Series & Forecasting
Module 1: Foundations & Setup
Series Intro To Time Series Data
Series Trends Seasonality Noise
Series Decomposition Techniques
Series Autoregressive Models AR
Series Moving Averages And Smoothing
Module 2: Core Architecture & Components
Series ARIMA And SARIMA Models
Series Feature Engineering For Dates
Series XGBoost For Forecasting
Series Prophet Library Basics
Series LSTMs For Time Series
Module 3: Advanced Capabilities & Workflows
Series 1D CNNs For Sequence Data
Series Transformer Models For Forecasting
Series Metrics MAE RMSE MAPE
Series Backtesting And Cross Validation
Series Deploying Forecasting Models
Module 4: Practical Implementation & Capstones
Series Capstone Stock Price Prediction
Building AI Applications & Products
Module 1: Foundations & Setup
Intro To AI Products
Choosing The Right API
Designing Chat Interfaces
Handling API Keys Securely
Streaming Responses In React
Module 2: Core Architecture & Components
Managing Conversation History
Building A Document Chat
Connecting A Vector Database
Handling Context Windows
Image Generation With Dalle
Module 3: Advanced Capabilities & Workflows
Voice Transcription With Whisper
Vision APIs For Image Analysis
Serverless Functions For AI
Caching And Rate Limiting
Monitoring API Costs
Module 4: Practical Implementation & Capstones
Capstone Fullstack AI Saa S
Recommender Systems
Module 1: Foundations & Setup
Sys Intro To Recommendation Engines
Sys Types Of Recommender Systems
Sys Data Collection Implicit Explicit
Sys Item Profiles And TFIDF
Sys Cosine Similarity For Items
Module 2: Core Architecture & Components
Sys Building A Content Based Model
Sys User User Collaborative Filtering
Sys Item Item Collaborative Filtering
Sys Matrix Factorization SVD
Sys Deep Learning For Recommendations
Module 3: Advanced Capabilities & Workflows
Sys Neural Collaborative Filtering
Sys Session Based Recommendations
Sys Metrics Precision Recall NDCG
Sys A B Testing Recommendations
Sys The Cold Start Problem
Module 4: Practical Implementation & Capstones
Sys Capstone Movie Recommendation Engine
Robotics & Autonomous Systems
Module 1: Foundations & Setup
Intro To Autonomous Agents
Sensors And Actuators Overview
The Sense Think Act Cycle
Forward And Inverse Kinematics
PID Controllers Explained
Module 2: Core Architecture & Components
Trajectory Planning
Stereo Vision And Depth
Li DAR And Radar Processing
Object Tracking In 3D
Intro To SLAM
Module 3: Advanced Capabilities & Workflows
Kalman Filters And Sensor Fusion
Particle Filters For Localization
Path Planning A Star And RRT
Intro To Robot Operating System ROS
Reinforcement Learning In Robotics
Module 4: Practical Implementation & Capstones
Capstone Simulating A Self Driving Car
Graph Neural Networks
Module 1: Foundations & Setup
Intro To Graphs And Networks
Nodes Edges And Adjacency Matrices
Graph Types Directed Undirected
Node Embeddings Deep Walk
Node2Vec And Random Walks
Module 2: Core Architecture & Components
Traditional Graph Features
Message Passing Neural Networks
Graph Attention Networks GAT
Graph Convolutional Networks GCN
Graph SAGE For Large Graphs
Module 3: Advanced Capabilities & Workflows
Heterogeneous Graps And Knowledge Graphs
Spatio Temporal Graphs
Molecular Chemistry And Drug Discovery
Social Network Analysis And Fraud
Traffic Prediction And Mapping
Module 4: Practical Implementation & Capstones
Capstone Recommendation With Graphs
Edge AI & TinyML
Module 1: Foundations & Setup
Intro To Edge Computing
Cloud vs Edge AI
Hardware For Edge AI
Model Quantization Basics
Pruning Neural Networks
Module 2: Core Architecture & Components
Knowledge Distillation
Intro To Tensor Flow Lite
Converting Models To TFLite
ONNX Runtime For Edge
Intro To Tiny ML And Arduino
Module 3: Advanced Capabilities & Workflows
Deploying Models To Microcontrollers
Optimizing Memory And Power
Real Time Object Detection On Mobile
Wake Word Detection For Voice
Capstone Smart Home Io T Sensor
Module 4: Practical Implementation & Capstones
Privacy Preserving Edge AI
Data Engineering for AI
Module 1: Foundations & Setup
Eng ETL Vs ELT Pipelines
Eng Intro To Data Engineering For AI
Eng Batch Vs Streaming Data
Eng Intro To Apache Spark
Eng Spark Data Frames And SQL
Module 2: Core Architecture & Components
Eng Distributed Computing Basics
Eng Intro To Apache Kafka
Eng Building A Kafka Producer
Eng Real Time Data Streaming
Eng Data Lakes Vs Data Warehouses
Module 3: Advanced Capabilities & Workflows
Eng Intro To Snowflake And Big Query
Eng Data Modeling Relational Vs No SQL
Eng Intro To Apache Airflow
Eng Building Airflow DAGs
Eng Orchestrating ML Pipelines
Module 4: Practical Implementation & Capstones
Eng Capstone Real Time Data Pipeline
Quantum Machine Learning
Module 1: Foundations & Setup
Intro To Quantum Mechanics
Qubits And Superposition
Quantum Entanglement And Gates
Quantum Circuits Basics
Grover And Shor Algorithms
Module 2: Core Architecture & Components
Variational Quantum Eigensolver VQE
Intro To Quantum Machine Learning
Quantum Support Vector Machines QSVM
Quantum Neural Networks QNN
Intro To Qiskit By IBM
Module 3: Advanced Capabilities & Workflows
Penny Lane For Quantum ML
Simulating Quantum Circuits
Quantum Approximate Optimization QAOA
Quantum Generative Adversarial Networks
Challenges In Quantum Hardware
👑 PRO
Module 4: Practical Implementation & Capstones
Capstone Building A Quantum Classifier
Python Data Science
Python
Python Variables & Dynamic Typing
Python String Manipulation
Python Arithmetic & Math Modules
Python Conditional Statements
Python For & While Loops
Python Functions
Python Lists (Mutable Sequences)
Python Tuples & Sets
Python Dictionaries (Key-Value Pairs)
Python Lambda Functions
Python List Comprehensions
Python Map, Filter & Reduce
Python Exception Handling
Python Reading & Writing Files
Python Environments & Conda
Python Jupyter & Colab
Python OS & Sys Libraries
Python API Basics
Python Automated Data Cleaner
Python AI Development Lifecycle
Numpy
Introduction to NumPy
Getting Started with NumPy
Creating NumPy Arrays
01. Fundamentals
NumPy Array Dimensions
NumPy Array Indexing
NumPy Array Slicing
NumPy Data Types
NumPy Copy vs View
NumPy Array Shape
NumPy Array Reshaping
NumPy Array Iterating
02. Advanced Array Manipulation
NumPy Array Joining
NumPy Array Splitting
NumPy Array Searching
NumPy Array Sorting
NumPy Filter Array
03. Random and Stats
NumPy Random Intro
NumPy Data Distribution
NumPy Random Permutations
Seaborn Visualization
Normal, Binomial, and Poisson
04. Universal Functions (ufunc)
NumPy ufuncs Intro
NumPy Create Your Own ufunc
NumPy Simple Arithmetic
NumPy Rounding Decimals
NumPy Logs and Summations
NumPy Matrix Algebra
Final NumPy Challenge
👑 PRO
Pandas
Introduction to Pandas
Pandas Getting Started
01. Core Data Structures
Pandas Series
Pandas DataFrames
02. Data I/O
Pandas Read CSV
Pandas Read JSON
Pandas Read Excel
Pandas Read SQL Databases
03. Data Cleaning
Pandas Data Analysis Intro
Pandas Cleaning Empty Cells
Pandas Cleaning Wrong Formats
Pandas Cleaning Wrong Data
Pandas Removing Duplicates
04. Data Analysis & Aggregation
Pandas Data Correlations
Pandas GroupBy Concepts
Pandas Aggregations
Pandas Window Functions
05. Relational Operations
Pandas Merging DataFrames
Pandas Joining DataFrames
Pandas Concatenation
Pandas Pivot Tables
Pandas Melting
06. Visualization
Pandas Plotting Data
Pandas Advanced Charts
Final Pandas Analytics Challenge
👑 PRO
Scipy
SciPy Introduction
Getting Started with SciPy
01. Constants and Optimization
SciPy Constants
SciPy Optimizers
SciPy Root Finding
02. Advanced Data Structures
SciPy Sparse Data
SciPy CSR and CSC Matrices
SciPy Graphs
03. Spatial Data & Statistics
SciPy Spatial Data
SciPy KD-Trees
SciPy Matlab Arrays
SciPy Interpolation
SciPy Significance Tests
Final SciPy Challenge
👑 PRO
TensorFlow
Introduction to Deep Learning
TensorFlow Basics
01. Core Architecture
Tensors and Constants
Variables and Math Operations
GradientTape and Autodiff
02. The Keras API
Sequential Models
Functional API
Custom Layers and Models
03. Training Fundamentals
Loss Functions
Optimizers (Adam, SGD, RMSprop)
Metrics and Evaluation
04. Advanced Network Types
Convolutional Neural Networks (CNN)
Recurrent Neural Networks (RNN)
LSTMs and Sequence Models
05. Regularization & Callbacks
Dropout and Regularization
Early Stopping and Callbacks
06. MLOps
Saving and Loading Models
TensorBoard Integration
Deep Learning Project
👑 PRO
Scikit-Learn & PyTorch
Machine Learning Concepts
01. Scikit-Learn Fundamentals
Loading Datasets
Data Preprocessing and Scalers
Building Pipelines
02. Supervised Learning
Linear and Logistic Regression
Support Vector Machines (SVM)
Decision Trees & Random Forests
03. Unsupervised & Evaluation
K-Means Clustering
PCA and Dimensionality Reduction
Cross-Validation and Grid Search
04. PyTorch Fundamentals
Introduction to PyTorch
PyTorch Tensors and Shapes
Autograd and Dynamic Graphs
05. Neural Networks in PyTorch
The nn.Module Class
Datasets and DataLoaders
Writing the Training Loop
06. PyTorch Advanced
CUDA and GPU Acceleration
Saving and Checkpointing Models
Final AI Architecture Challenge
👑 PRO
Cloud
AWS
01. Cloud Foundations
Introduction to Cloud Computing (IaaS, PaaS, SaaS)
AWS Global Infrastructure (Regions, AZs, Edge Locations)
The Shared Responsibility Model
AWS Free Tier & Account Setup
02. IAM & Security
Introduction to IAM (Identity & Access Management)
Users, Groups, and Policies (JSON)
IAM Roles vs. User Credentials
Multi-Factor Authentication (MFA) & Root Account Security
AWS CLI & SDK Setup
03. Compute (EC2)
Launching an EC2 Instance
Security Groups (Firewall Rules)
Private vs. Public IPs & SSH (Key Pairs)
EBS Volumes (Elastic Block Store) & Snapshots
AMIs (Amazon Machine Images)
EC2 Pricing Models (On-Demand, Spot, Reserved)
👑 PRO
04. Storage (S3)
Introduction to S3 (Buckets & Objects)
S3 Storage Classes (Standard, Intelligent-Tiering, Glacier)
Versioning & Lifecycle Policies
S3 Security (Bucket Policies & Encryption)
Static Website Hosting on S3
Storage Gateway & Snow Family (Data Migration)
05. Networking (VPC)
Introduction to VPC (Virtual Private Cloud)
Subnets (Public vs. Private) & CIDR Blocks
Internet Gateway (IGW) & Route Tables
NAT Gateways & Bastion Hosts
VPC Peering & Endpoints
06. High Availability
Elastic Load Balancing (ALB vs. NLB)
Auto Scaling Groups (ASG)
Route 53 (DNS Management & Routing Policies)
07. Databases
RDS (Relational Database Service) Fundamentals
RDS Multi-AZ vs. Read Replicas
Aurora (Serverless & Global)
DynamoDB (NoSQL Key-Value Store)
ElastiCache (Redis & Memcached)
08. Serverless & App Services
Introduction to AWS Lambda
Triggering Lambda from S3/API Gateway
API Gateway (REST & HTTP APIs)
SQS (Simple Queue Service) Decoupling
SNS (Simple Notification Service)
09. Containers & DevOps
Introduction to Docker on AWS
ECS (Elastic Container Service) & Fargate
ECR (Elastic Container Registry)
Infrastructure as Code: CloudFormation Basics
CI/CD on AWS (CodePipeline, CodeBuild, CodeDeploy)
10. Monitoring & Management
CloudWatch (Metrics, Logs, Alarms)
EventBridge (CloudWatch Events)
CloudTrail (Auditing & Governance)
AWS Systems Manager (SSM)
11. Architecture & Cost
The Well-Architected Framework Pillars
AWS Trusted Advisor
AWS Cost Explorer & Budgets
Disaster Recovery Strategies
Back End
Node
Node Essentials Concepts
Node What is
Node Event Loop and non-blocking I/O
Node CommonJS vs ES Modules
Node Global Objects
Node Internal Modules
Node NPM and Dependencies
Node Introduccion Package.json
Node Advance Concepts
Node Streams and Buffers
Node Worker Threads and Child Processes
Node Memory Management and Garbage Collection
Node Clustering
Node Patters Middleware
Node Custom EventEmitters
Node Building Backend Systems
Node Layers Architecture (controllers, services, models)
Node Split Responsabilities
Node Express.js (router, middleware)
Node Database Connection (MongoDB with Mongoose and PostgreSQL with Sequelize/Knex)
Node Authentication and Authorization (JWT, OAuth)
Node Global Error Handling
Node Logging and Catching
Node Logging Practice
👑 PRO
Node Introduction Redis
Node Cache Manual vs Automatic
Node Cache Invalid Strategies
Node Redis Sessions
Node REST APIs
Node Express Routes and Controllers
Node Validation Data with Joi/Yup
Node API Versions
Node Documentation with Swagger/OpenAPI
Node Security: CORS, Rate Limiting, Headers HTTP
GraphQL with Node.js
Node Intro to GraphQL
Schema, Queries, Mutations y Resolvers
Node Apollo Server
Node Data Base Integration
Node Autenticationn in GraphQL
Node Comparative REST
Testing in Node.js
Node Test Types: E2E, Unit, Integration
Node Mocha + Chai / Jest
Node Mocking and spies (with Sinon.js or Jest)
Create Dockerfile for Node.js
Node Intro Docker
Node .Dockerignore use
Node Docker Compose (multi-container apps)
Node Network and Data Persistance
Node Dev Environments and Volumes
Node Deployment Applications
Real Time Chat with WebSockets
SQL
SQL Introduction
Database Concepts
DBMS Overview
Environment Setup
DMBS Tools Usage
First Connections and Steps
SQL Basic Commands
SQL Fundamentals
SELECT
WHERE
ORDER BY
LIMIT
Conditionals and Aggregation Functions
Comparison Operators
AND, OR, NOT
COUNT, SUM, AVG, MIN, MAX
Group By
Having
Data Manipulation Language (DML)
INSERT INTO
UPDATE
DELETE
DROP, COMMIT, ROLLBACK
Management
juniorToMid
Core Technologies Advance-Knowledge
Accessibility Semantic HTML
Advanced CSS
Modern Frameworks and Libraries
Testing
Modern Libraries Frameworks
Optimization and Build
Version Control
Dev Methodologies
Team Work and Communication
Problem solving
Scrum
Introduction to Scrum
Fundamentals of Scrum
Scrum Framework
Roles in Scrum
The Scrum Master
Scrum Events in Detail
Artifacts and Transparency in Scrum
Scaling Scrum
PSM I Certification (Professional Scrum Master I)
Exam Preparation
Practical Application of Scrum
Product Management
01. PM Fundamentals
Introduction to Digital Product Management
Product Lifecycle
Roles in Tech: PM vs Project Manager vs Product Owner
👑 PRO
Key Skills: Soft Skills and Hard Skills
Development Methodologies (Waterfall vs Agile)
02. Discovery
Problem and Opportunity Identification
User Research
Qualitative Interviews and Surveys
Competitive Analysis (Benchmarking)
Creating User Personas
Empathy Maps
03. Product Strategy
Product Vision and Mission Definition
Value Proposition Canvas
Objectives and Key Results (OKRs)
Business Model Canvas & Lean Canvas
Stakeholder Management
04. Definition and Roadmap
Feature Prioritization (RICE, MoSCoW, Kano)
Product Roadmap Creation
MVP Definition (Minimum Viable Product)
Product KPIs and Success Metrics
05. Design and UX
UX/UI Fundamentals for PMs
User Journey Mapping
Wireframing and Prototyping (Low vs High fidelity)
Usability Testing
Collaboration with Designers
06. Technical Execution
Working with Engineering Teams
Writing User Stories
Acceptance Criteria
Backlog Management (Refinement/Grooming)
Scrum Rituals (Sprint Planning, Daily, Retro)
07. Launch and Marketing
Go-to-Market Strategy (GTM)
Positioning and Messaging
Launch Plan (Launch Checklist)
Collaboration with Sales and Marketing
08. Metrics and Growth
Product Analytics (Mixpanel, Google Analytics)
Pirate Metrics (AARRR: Acquisition, Activation, etc.)
Retention and Churn Analysis
A/B Testing and Experimentation
Iteration and Feedback Loops
09. Career and Leadership
Building a Product Portfolio
PM Interview Preparation
Leadership without Authority
Digital Marketing
AI for Digital Marketers
01. AI Foundations
Introduction to AI in Marketing
Generative AI vs. Predictive AI
The AI Marketing Landscape (Tools Overview)
Ethics, Copyright, and Brand Safety
02. Prompt Engineering
Basics of Prompting (Context, Task, Persona)
Zero-shot vs. Few-shot Prompting
Iterative Refinement for Better Outputs
Building a Brand Voice Library
03. Content Marketing
Brainstorming and Ideation with AI
Writing Long-form Blog Posts (SEO-driven)
Repurposing Content (e.g., Blog to LinkedIn)
Editing and Polishing Content
04. Copywriting & Ads
Writing High-Converting Ad Copy (Meta/Google)
Generating Headlines and Hooks
Creating Landing Page Copy
A/B Testing Copy Variations with AI
05. AI for Design & Video
Introduction to AI Image Generators (Midjourney/DALL-E)
Prompting for Specific Visual Styles
AI in Design Tools (Canva Magic Studio, Adobe Firefly)
AI Video Creation (Script-to-Video tools)
AI Voiceovers and Avatars (ElevenLabs, HeyGen)
06. Social Media Strategy
Creating Monthly Content Calendars
Generating Viral Hooks and Captions
Automating Social Interaction (Chatbots)
Trend Analysis with AI
07. SEO & Research
Keyword Research and Clustering with AI
Competitor Analysis and Summarization
Creating User Personas with AI
Generating Schema Markup and Meta Tags
08. Email Marketing
Personalization at Scale
Writing Cold Outreach Emails
Subject Line Optimization
Automated Drip Campaign Structures
09. Data & Analytics
Analyzing Customer Data (ChatGPT Data Analyst)
Sentiment Analysis of Reviews
Predictive Analytics for Marketers (No-Code)
Reporting and Visualization Helpers
10. Workflow & Integration
Building an AI Marketing Stack
Automating Workflows (Zapier/Make + OpenAI)
Future of AI in Marketing
AI Art Direction & Creative Workflows
Fundamentals and Ethics
Design vs AI Direction
AI Legal & Copyright Basics
Intellectual Property EU/USA
AI Bias & Visual Stereotypes
Photography Terms for Prompting
Lighting & Composition Rules
Midjourney v6 Intro
Midjourney Parameters (--s, --w, --no)
Midjourney Aspect Ratios (--ar)
Advanced Prompting Structure
Prompt Layering: Subject + Env + Light
Character Consistency (--cref)
Style Consistency (--sref)
DALL-E 3 Vision & Iteration
Stable Diffusion Concepts
Open Source vs Closed Models
Intro to ControlNet
Pose Guidance & Skeletal Mapping
Sketch to Image
Inpainting Basics
Generative Expand (Outpainting)
Fixing Details: Hands & Eyes
AI Upscaling Tools
Magnific AI Workflow
High Res & Print Quality
Photoshop Generative Fill
Firefly Integration
Illustrator Text to Vector
AI Vector Logos & Icons
The Sandwich Workflow
Human-AI-Human Handoff
Text-to-Video Intro
Runway Gen-2 & Gen-3
Pika Labs Controls
Image-to-Video Animation
AI Lip Sync Tools
Avatars with HeyGen
Sync Labs Integration
Brand Consistency Challenges
👑 PRO
Intro to LoRAs
Training Custom Models
Face Training (Leonardo AI)
Style Training for Brands
LoRA Implementation
Campaign 360 Briefing
AI Visual Identity Setup
AI Product Photography
AI Commercial Spot (15s)
👑 PRO
Final Workflow Defense
👑 PRO

Quick References

Technical Resources

Resource Hub

Insights

Our Blog

Community

Useful Links

Code Syllabus

Courses Catalog

Front End
HTML
HTML Intro
How Works HTML
HTML Tools
HTML First Document
HTML Basic Structure
HTML Code in the HTML Browser
HTML Tags
HTML Tags and Attributes
HTML Common Tags: <div>, <span>, <h1>-<h6>, <p>, <br>, <hr>
HTML Lists
HTML Ordered Lists (<ol>, <li>)
HTML Unordered Lists (<ul>, <li>)
HTML Images in HTML: <img>
HTML Insert Images <img>
Intro to Semantic Tags
HTML Semantic Tags
HTML Meta Tags and SEO
HTML Character Encoding and the <meta> Tag
HTML Links
html Creating Links <a>
HTML Link Attributes: href and target
HTML Internal and External Links
HTML Email Links in HTML (mailto:)
HTML Tables
HTML Creating a Table (<table>, <tr>, <td>, <th>)
HTML Table Attributes: border, cellpadding, cellspacing
HTML Creating Table Headers and Merged Cells
HTML Forms
HTML Form Structure (<form>)
HTML Form Fields (<input type="text">, password, submit)
HTML Buttons (<button>, input type="button")
HTML Select Fields (<select>, <option>)
HTML Checkboxes and Radios (<input type="checkbox">, radio)
HTML Multimedia Elements
HTML Adding Video: <video>, attributes controls, autoplay, loop
HTML Adding Audio: <audio>, attributes controls, autoplay, loop
HTML Using <iframe> in HTML
HTML Semantic Tags: <header>, <nav>, <section>, <article>, <aside>, <footer>
HTML Titles and Favicons (<title>, <link>)
HTML Comments
HTML Links and Navigation
HTML Navigation Menus
HTML5 and Browser API
HTML Geolocation API
Local Storage API (localStorage)
HTML Validation
Using HTML Validators
HTML Common Errors and How to Fix Them
HTML Mastery Quiz
CSS
Introduction to CSS
CSS Syntax
CSS Incorporation
CSS Basic Selectors
CSS Colors
CSS Fonts and Text
CSS Text Alignment
CSS Background Properties
CSS Gradients
CSS Background Image
Box Model
CSS Width and Height
CSS Margin and Padding
CSS Borders
CSS Box Sizing
CSS Overflow
CSS Display
CSS Positioning
CSS Z-Index
CSS Float
CSS Alignment
CSS Flexbox Intro
CSS Flexbox Container
CSS Flex Direction
CSS Justify Content
CSS Align Items
CSS Flex Wrap
CSS Flexbox Items
CSS Display Grid
CSS Grid Columns
CSS Grid Rows
CSS Grid Gap
CSS Grid Area
CSS Relative Units
CSS Media Queries
CSS Responsive Design
CSS Frameworks
CSS Transitions and Animations
CSS Keyframes
CSS Advanced Effects
CSS Foundations Quiz
JavaScript
JavaScript Introduction
JavaScript Basic Syntax
JavaScript Operators
JavaScript Comments
JavaScript Control Structure
JavaScript Conditionals
JavaScript Loops
JavaScript Functions
Declaration, anonymous and arrow functions
JavaScript Return Arguments and Parameters
JavaScript Scope
JavaScript Arrays and Objects
JavaScript Objects
JavaScript Common Methods (push, map, filter)
JavaScript Array Loops (for, forEach)
JavaScript DOM (Document Object Model)
JavaScript Manipulatio (getElementById, innerHTML)
JavaScript Style Modification
JavaScript Events addEventListener
JavaScript BOM (Browser Object Model)
Objetos: window, document, location, history
JavaScript Windows Manipulation and Redirects
JavaScript Advance Functions
Javacript HOC, Closures, and recursivity
JavaScript Callback Functions
JavaScript Object-Oriented Programming(OOP)
Classes, Inheritance, Constructors
JavaScript Prototypes and Inherance
JavaScript Async Function and Promises
Introduction to Asynchronous Programming
JavaScript Promises (then, catch) and use of async/await
JavaScript Events
JavaScript Common Events: mouse, keyboard and forms
JavaScript Propagation and events delegation
JavaScript Dates and Time
JavaScript Dates and Methods
JavaScript setTimeout y setInterval
JavaScript JSON, Manipulation Data and API
JavaScript JSON Works (JSON.stringify, JSON.parse)
JavaScript Fetch API for HTTP request (GET, POST)
JavaScript Storage
localStorage, sessionStorage, y cookies
JavaScript Modules
JavaScript Export and import modules (export, import)
JavaScript Modular Code
JavaScript Errors and Debugging
JavaScript Errors (try, catch, throw)
JavaScript Debugging Tools
JavaScript Logic Quiz
React
React Introduction
React Components Intro
React Tools
React Introduction Jsx
React First Steps
React Structure
React Components, Props, State
React JSX
Difference Function vs Class
React Components
React Functional Components
React Props
React State with useState
React Class Components
React Re-use Components
React Communication Between Components
React JSX Advance
React Syntax JSX
React JSX Expressions
React inline and Class Styles
React Loops and Conditionals
React Fragments
React State Management
React State Intro
React Local State vs Global State
React useState
React Forms and state Management inputs
React Hooks
React useEffect
React useContext
React useRef
React useReducer
React Custom Hooks
React Events
Eventos common: onClick, onChange, onSubmit, etc.
Eventos sintéticos React
React PreventDefault
React Conditional Rendering and Lists
React Conditional Render
React map()
React key in List
React Render
React CSS Style
React inline and Class Styles
React CSS Modules
React Dynamic Style
React Style Libraries
React Router
React-router-dom
React Dynamic Routes
React Route, Switch, y Link
React URL
React useHistory
Redux Intro
Redux Install
React Store, Actions, Reducers
React Redux Hooks
React Forms
React APIs
React HttpAxios
React LazySuspense
React Condicional vs Lazy vs Suspense
React React.memo y useMemo
Angular
Angular Introduction
Angular Architecture
Create Angular Project
👑 PRO
Angular Components
Template, style and logic
Data Binding Angular
Event Binding Angular
Directives Intro
Structural Directives
Attribute Directives
Custom Directives
Services and DI Intro
Angular Services
Angular Injectables
Singleton Services
Navigation and Routing Intro
Routes Configuration
Routing and Navigation
Dynamic Routes and Parameters
Child Routes & Lazy Loading
Angular Forms Intro
Template-Driven Forms
Reactive Forms & Validation
HTTP & API Consumption
HttpClient & Configuration
RESTful HTTP Requests
HTTP Error Handling
RxJS Introduction
Observables & Lifecycle
RxJS Operators Mastery
The Async Pipe
Angular Modules (NgModules)
Standalone Components
Advanced Dependency Injection
Component Lifecycle Mastery
Testing Foundations
Component Testing Mastery
Service & Logic Testing
Launch: Deploy & Optimize
Vue
What is Vue?
Setup & The App Instance
Reactivity: ref vs reactive
Computed Properties
Methods & Event Handling
Two-Way Binding (v-model)
Conditional Rendering
List Rendering
Lifecycle Hooks
Components & Props
Slots
Watchers
Provide / Inject
Composables
Vue Router Intro
Three
Introduction to WebGL & Three.js
Creating a Scene
Cameras & Perspectives
The WebGL Renderer
Geometries
Materials
Meshes & Transformations
Lighting
Shadows
Textures & Mapping
The Animation Loop
Orbit Controls
Particles & Sprites
Importing 3D Models
Raycaster & Interaction
Physics Integration
Custom Shaders
Build Apps with AI
Responsive and Accessible Interface Design
Forms and User Input Handling (Prompts)
API Requests and Middleware
Connecting with OpenAI and Hugging Face APIs
Real-time AI Content Rendering
Loading States and UX in AI Applications
Topic 3: Machine Learning in the Browser
TensorFlow.js Fundamentals
Introduction to Client-side Machine Learning
Advantages of Running ML in the Browser (Low Latency)
Using Pre-trained Models
Implementing ML Logic with JavaScript
Running Predictions without a Server
Building Data Pipelines in the Browser
AI Data Visualization
Testing and Debugging AI Functions
Topic 4: Deployment and Final Project (Capstone)
👑 PRO
Deployment Platforms: Vercel, Render and AWS
Production Configuration
Cost Optimization and API Usage
Performance Monitoring
Logging Model Calls
Ethical UX Design
Mitigating Bias in AI Responses
Capstone Project: Planning and Architecture
👑 PRO
Capstone Project: Development of Complete AI Web Application
👑 PRO
Capstone Project: Presentation and Functional Demo
👑 PRO
Artificial Intelligence
AI Foundations
01. AI Foundations
Introduction to Artificial Intelligence & History
AI vs. Machine Learning vs. Deep Learning
Python for Data Science (NumPy, Pandas Review)
Data Visualization (Matplotlib, Seaborn)
Setting up the Environment (Jupyter, Google Colab)
02. Data Processing
Exploratory Data Analysis (EDA)
Data Cleaning and Handling Missing Values
Feature Scaling and Normalization
Feature Encoding (One-Hot, Label Encoding)
Splitting Data (Train/Test/Validation Sets)
03. Supervised Learning
Introduction to Supervised Learning
Linear Regression (Simple & Multiple)
Logistic Regression
Decision Trees and Random Forests
Support Vector Machines (SVM)
Evaluation Metrics (RMSE, Accuracy, Precision, Recall, F1)
04. Unsupervised Learning
Introduction to Unsupervised Learning
K-Means Clustering
Hierarchical Clustering
Dimensionality Reduction (PCA)
Recommender Systems Basics
05. Neural Networks (Deep Learning)
Introduction to Artificial Neural Networks (ANN)
Perceptrons and Activation Functions (ReLU, Sigmoid)
Forward Propagation vs. Backpropagation
Loss Functions and Optimizers (Adam, SGD)
Handling Overfitting (Dropout, Regularization)
06. Computer Vision
Introduction to Convolutional Neural Networks (CNN)
Building CNNs with TensorFlow/Keras or PyTorch
Image Augmentation Techniques
Transfer Learning (VGG16, ResNet)
Object Detection Basics (YOLO intro)
07. Natural Language Processing (NLP)
Text Preprocessing (Tokenization, Stemming, Lemmatization)
Bag of Words & TF-IDF
Word Embeddings (Word2Vec, GloVe)
Recurrent Neural Networks (RNN) & LSTMs
Introduction to Transformers (Attention Mechanism)
08. Generative AI & LLMs
Introduction to Large Language Models (LLMs)
Prompt Engineering Strategies
Using OpenAI / Anthropic APIs
Retrieval-Augmented Generation (RAG) Basics
Image Generation (Diffusion Models Intro)
09. Deployment & Ethics
Saving and Loading Models (Pickle, Joblib)
Creating an API with FastAPI/Flask
Containerization (Docker Basics for AI)
AI Ethics: Bias, Fairness, and Explainability
Future Trends in AI
Automation
01. Automation Foundations
Introduction to Low-Code & No-Code Automation
Understanding APIs, Webhooks, and API Keys
Data Structures 101: JSON for Marketers
The Landscape: n8n vs. Make (Integromat) vs. Zapier
Setting up OpenAI API & Anthropic API
02. Getting Started with n8n
02. Getting Started with n8n
Installing n8n (Cloud vs. Self-Hosted/Docker)
The n8n Interface: Nodes, Connections, and Workflows
Understanding the Trigger Node
Core Nodes: Set, IF, Switch, and Merge
Your First Workflow: Form to Email/Slack Notification
03. AI Content Engines
Building an Idea-to-Article Generator
Integrating Search (SerpApi) for SEO-Driven AI Content
Automated WordPress Publishing via n8n
Image Generation Pipeline (Midjourney/DALL-E API)
Repurposing: Converting YouTube Transcripts to Blog Posts
04. Social Media Automation
Automated Social Listening & Sentiment Analysis
Content Distribution: Auto-posting to LinkedIn/X/Instagram
AI Comment Generator for Engagement
Dynamic Image Creation for Social (Bannerbear + AI)
05. Lead Gen & CRM Ops
Connecting Lead Forms (Typeform/Facebook) to CRMs (HubSpot)
👑 PRO
Automated Lead Enrichment (Clearbit/Apollo + AI Scraping)
AI Lead Scoring: Grading Leads based on Data
Personalized Cold Outreach Generation
06. Advanced n8n Logic
Working with Arrays and Loops (Item Lists)
The HTTP Request Node: Connecting to Any API
The Code Node: Basic JavaScript for Data Transformation
Error Handling and Retry Strategies
Webhooks: Receiving Real-time Data
07. Email & Support Automation
Auto-Categorizing Incoming Emails (Support vs. Sales)
AI Draft Replies for Customer Support (Human-in-the-loop)
Weekly Newsletter Compilation (RSS + AI Summarizer)
08. Building AI Agents
Introduction to LangChain in n8n
Creating a Chatbot with Memory
RAG Basics: Chatting with your own PDF/Notion Data
Web Scraping Agents (Puppeteer/ScrapingBee)
09. Operations & Scale
Database Syncing (Google Sheets / Airtable / PostgreSQL)
Document Parsing (PDF Invoice to Data)
Managing API Costs and Rate Limits
Security Best Practices for Automations
👑 PRO
MLOps & Model Deployment
Module 1: Foundations & Setup
Intro To Machine Learning Operations
The ML Lifecycle
Version Control For Data DVC
Intro To Docker For ML
Creating Dockerfiles For Models
Module 2: Core Architecture & Components
Docker Compose For ML Apps
Building Fast API For Models
REST vs g RPC For Model Serving
Intro To Tensor Flow Serving
Continuous Integration For ML
Module 3: Advanced Capabilities & Workflows
Git Hub Actions For ML Pipelines
Automated Model Testing
Model Drift And Data Drift
Monitoring With Prometheus Grafana
A B Testing For ML Models
Module 4: Practical Implementation & Capstones
Capstone End To End Deployment
Reinforcement Learning
Module 1: Foundations & Setup
Intro To Reinforcement Learning
Markov Decision Processes MDPs
Dynamic Programming Basics
Rewards And Return
Monte Carlo Methods
Module 2: Core Architecture & Components
Temporal Difference Learning TD
Q Learning Explained
Intro To Deep Q Networks DQN
Experience Replay And Target Networks
Policy Gradient Methods REINFORCE
Module 3: Advanced Capabilities & Workflows
Actor Critic Methods
Proximal Policy Optimization PPO
Soft Actor Critic SAC
Intro To Open AI Gym Gymnasium
Building Custom Environments
Module 4: Practical Implementation & Capstones
Multi Agent Reinforcement Learning
Capstone Train AI To Play A Game
AI Ethics, Safety & Alignment
Module 1: Foundations & Setup
Intro To AI Ethics
History Of AI Failures
The Alignment Problem
Understanding Algorithmic Bias
Measuring Fairness In Models
Module 2: Core Architecture & Components
Mitigating Bias Techniques
Intro To Explainable AI
LIME And SHAP Values
Data Privacy Laws GDPR
Federated Learning Basics
Module 3: Advanced Capabilities & Workflows
Interpreting Deep Learning Models
Adversarial Attacks On AI
AI Regulations EU AI Act
Corporate AI Guidelines
Future Of AGI And Society
Module 4: Practical Implementation & Capstones
Capstone Auditing An AI System
Audio & Speech Processing
Module 1: Foundations & Setup
Intro To Sound Waves
Digital Audio And Sampling
Working With Librosa
Spectrograms And Mel Scale
MFCCs Explained
Module 2: Core Architecture & Components
Zero Crossing Rate And Energy
Intro To Speech To Text
Hidden Markov Models HMM
Deep Learning For ASR Wav2Vec
Intro To Text To Speech
Module 3: Advanced Capabilities & Workflows
Vocoders And Spectrogram Inversion
Modern TTS Tacotron
Environmental Sound Recognition
Music Genre Classification
Voice Activity Detection VAD
Module 4: Practical Implementation & Capstones
Capstone Voice Command Assistant
Time Series & Forecasting
Module 1: Foundations & Setup
Series Intro To Time Series Data
Series Trends Seasonality Noise
Series Decomposition Techniques
Series Autoregressive Models AR
Series Moving Averages And Smoothing
Module 2: Core Architecture & Components
Series ARIMA And SARIMA Models
Series Feature Engineering For Dates
Series XGBoost For Forecasting
Series Prophet Library Basics
Series LSTMs For Time Series
Module 3: Advanced Capabilities & Workflows
Series 1D CNNs For Sequence Data
Series Transformer Models For Forecasting
Series Metrics MAE RMSE MAPE
Series Backtesting And Cross Validation
Series Deploying Forecasting Models
Module 4: Practical Implementation & Capstones
Series Capstone Stock Price Prediction
Building AI Applications & Products
Module 1: Foundations & Setup
Intro To AI Products
Choosing The Right API
Designing Chat Interfaces
Handling API Keys Securely
Streaming Responses In React
Module 2: Core Architecture & Components
Managing Conversation History
Building A Document Chat
Connecting A Vector Database
Handling Context Windows
Image Generation With Dalle
Module 3: Advanced Capabilities & Workflows
Voice Transcription With Whisper
Vision APIs For Image Analysis
Serverless Functions For AI
Caching And Rate Limiting
Monitoring API Costs
Module 4: Practical Implementation & Capstones
Capstone Fullstack AI Saa S
Recommender Systems
Module 1: Foundations & Setup
Sys Intro To Recommendation Engines
Sys Types Of Recommender Systems
Sys Data Collection Implicit Explicit
Sys Item Profiles And TFIDF
Sys Cosine Similarity For Items
Module 2: Core Architecture & Components
Sys Building A Content Based Model
Sys User User Collaborative Filtering
Sys Item Item Collaborative Filtering
Sys Matrix Factorization SVD
Sys Deep Learning For Recommendations
Module 3: Advanced Capabilities & Workflows
Sys Neural Collaborative Filtering
Sys Session Based Recommendations
Sys Metrics Precision Recall NDCG
Sys A B Testing Recommendations
Sys The Cold Start Problem
Module 4: Practical Implementation & Capstones
Sys Capstone Movie Recommendation Engine
Robotics & Autonomous Systems
Module 1: Foundations & Setup
Intro To Autonomous Agents
Sensors And Actuators Overview
The Sense Think Act Cycle
Forward And Inverse Kinematics
PID Controllers Explained
Module 2: Core Architecture & Components
Trajectory Planning
Stereo Vision And Depth
Li DAR And Radar Processing
Object Tracking In 3D
Intro To SLAM
Module 3: Advanced Capabilities & Workflows
Kalman Filters And Sensor Fusion
Particle Filters For Localization
Path Planning A Star And RRT
Intro To Robot Operating System ROS
Reinforcement Learning In Robotics
Module 4: Practical Implementation & Capstones
Capstone Simulating A Self Driving Car
Graph Neural Networks
Module 1: Foundations & Setup
Intro To Graphs And Networks
Nodes Edges And Adjacency Matrices
Graph Types Directed Undirected
Node Embeddings Deep Walk
Node2Vec And Random Walks
Module 2: Core Architecture & Components
Traditional Graph Features
Message Passing Neural Networks
Graph Attention Networks GAT
Graph Convolutional Networks GCN
Graph SAGE For Large Graphs
Module 3: Advanced Capabilities & Workflows
Heterogeneous Graps And Knowledge Graphs
Spatio Temporal Graphs
Molecular Chemistry And Drug Discovery
Social Network Analysis And Fraud
Traffic Prediction And Mapping
Module 4: Practical Implementation & Capstones
Capstone Recommendation With Graphs
Edge AI & TinyML
Module 1: Foundations & Setup
Intro To Edge Computing
Cloud vs Edge AI
Hardware For Edge AI
Model Quantization Basics
Pruning Neural Networks
Module 2: Core Architecture & Components
Knowledge Distillation
Intro To Tensor Flow Lite
Converting Models To TFLite
ONNX Runtime For Edge
Intro To Tiny ML And Arduino
Module 3: Advanced Capabilities & Workflows
Deploying Models To Microcontrollers
Optimizing Memory And Power
Real Time Object Detection On Mobile
Wake Word Detection For Voice
Capstone Smart Home Io T Sensor
Module 4: Practical Implementation & Capstones
Privacy Preserving Edge AI
Data Engineering for AI
Module 1: Foundations & Setup
Eng ETL Vs ELT Pipelines
Eng Intro To Data Engineering For AI
Eng Batch Vs Streaming Data
Eng Intro To Apache Spark
Eng Spark Data Frames And SQL
Module 2: Core Architecture & Components
Eng Distributed Computing Basics
Eng Intro To Apache Kafka
Eng Building A Kafka Producer
Eng Real Time Data Streaming
Eng Data Lakes Vs Data Warehouses
Module 3: Advanced Capabilities & Workflows
Eng Intro To Snowflake And Big Query
Eng Data Modeling Relational Vs No SQL
Eng Intro To Apache Airflow
Eng Building Airflow DAGs
Eng Orchestrating ML Pipelines
Module 4: Practical Implementation & Capstones
Eng Capstone Real Time Data Pipeline
Quantum Machine Learning
Module 1: Foundations & Setup
Intro To Quantum Mechanics
Qubits And Superposition
Quantum Entanglement And Gates
Quantum Circuits Basics
Grover And Shor Algorithms
Module 2: Core Architecture & Components
Variational Quantum Eigensolver VQE
Intro To Quantum Machine Learning
Quantum Support Vector Machines QSVM
Quantum Neural Networks QNN
Intro To Qiskit By IBM
Module 3: Advanced Capabilities & Workflows
Penny Lane For Quantum ML
Simulating Quantum Circuits
Quantum Approximate Optimization QAOA
Quantum Generative Adversarial Networks
Challenges In Quantum Hardware
👑 PRO
Module 4: Practical Implementation & Capstones
Capstone Building A Quantum Classifier
Python Data Science
Python
Python Variables & Dynamic Typing
Python String Manipulation
Python Arithmetic & Math Modules
Python Conditional Statements
Python For & While Loops
Python Functions
Python Lists (Mutable Sequences)
Python Tuples & Sets
Python Dictionaries (Key-Value Pairs)
Python Lambda Functions
Python List Comprehensions
Python Map, Filter & Reduce
Python Exception Handling
Python Reading & Writing Files
Python Environments & Conda
Python Jupyter & Colab
Python OS & Sys Libraries
Python API Basics
Python Automated Data Cleaner
Python AI Development Lifecycle
Numpy
Introduction to NumPy
Getting Started with NumPy
Creating NumPy Arrays
01. Fundamentals
NumPy Array Dimensions
NumPy Array Indexing
NumPy Array Slicing
NumPy Data Types
NumPy Copy vs View
NumPy Array Shape
NumPy Array Reshaping
NumPy Array Iterating
02. Advanced Array Manipulation
NumPy Array Joining
NumPy Array Splitting
NumPy Array Searching
NumPy Array Sorting
NumPy Filter Array
03. Random and Stats
NumPy Random Intro
NumPy Data Distribution
NumPy Random Permutations
Seaborn Visualization
Normal, Binomial, and Poisson
04. Universal Functions (ufunc)
NumPy ufuncs Intro
NumPy Create Your Own ufunc
NumPy Simple Arithmetic
NumPy Rounding Decimals
NumPy Logs and Summations
NumPy Matrix Algebra
Final NumPy Challenge
👑 PRO
Pandas
Introduction to Pandas
Pandas Getting Started
01. Core Data Structures
Pandas Series
Pandas DataFrames
02. Data I/O
Pandas Read CSV
Pandas Read JSON
Pandas Read Excel
Pandas Read SQL Databases
03. Data Cleaning
Pandas Data Analysis Intro
Pandas Cleaning Empty Cells
Pandas Cleaning Wrong Formats
Pandas Cleaning Wrong Data
Pandas Removing Duplicates
04. Data Analysis & Aggregation
Pandas Data Correlations
Pandas GroupBy Concepts
Pandas Aggregations
Pandas Window Functions
05. Relational Operations
Pandas Merging DataFrames
Pandas Joining DataFrames
Pandas Concatenation
Pandas Pivot Tables
Pandas Melting
06. Visualization
Pandas Plotting Data
Pandas Advanced Charts
Final Pandas Analytics Challenge
👑 PRO
Scipy
SciPy Introduction
Getting Started with SciPy
01. Constants and Optimization
SciPy Constants
SciPy Optimizers
SciPy Root Finding
02. Advanced Data Structures
SciPy Sparse Data
SciPy CSR and CSC Matrices
SciPy Graphs
03. Spatial Data & Statistics
SciPy Spatial Data
SciPy KD-Trees
SciPy Matlab Arrays
SciPy Interpolation
SciPy Significance Tests
Final SciPy Challenge
👑 PRO
TensorFlow
Introduction to Deep Learning
TensorFlow Basics
01. Core Architecture
Tensors and Constants
Variables and Math Operations
GradientTape and Autodiff
02. The Keras API
Sequential Models
Functional API
Custom Layers and Models
03. Training Fundamentals
Loss Functions
Optimizers (Adam, SGD, RMSprop)
Metrics and Evaluation
04. Advanced Network Types
Convolutional Neural Networks (CNN)
Recurrent Neural Networks (RNN)
LSTMs and Sequence Models
05. Regularization & Callbacks
Dropout and Regularization
Early Stopping and Callbacks
06. MLOps
Saving and Loading Models
TensorBoard Integration
Deep Learning Project
👑 PRO
Scikit-Learn & PyTorch
Machine Learning Concepts
01. Scikit-Learn Fundamentals
Loading Datasets
Data Preprocessing and Scalers
Building Pipelines
02. Supervised Learning
Linear and Logistic Regression
Support Vector Machines (SVM)
Decision Trees & Random Forests
03. Unsupervised & Evaluation
K-Means Clustering
PCA and Dimensionality Reduction
Cross-Validation and Grid Search
04. PyTorch Fundamentals
Introduction to PyTorch
PyTorch Tensors and Shapes
Autograd and Dynamic Graphs
05. Neural Networks in PyTorch
The nn.Module Class
Datasets and DataLoaders
Writing the Training Loop
06. PyTorch Advanced
CUDA and GPU Acceleration
Saving and Checkpointing Models
Final AI Architecture Challenge
👑 PRO
Cloud
AWS
01. Cloud Foundations
Introduction to Cloud Computing (IaaS, PaaS, SaaS)
AWS Global Infrastructure (Regions, AZs, Edge Locations)
The Shared Responsibility Model
AWS Free Tier & Account Setup
02. IAM & Security
Introduction to IAM (Identity & Access Management)
Users, Groups, and Policies (JSON)
IAM Roles vs. User Credentials
Multi-Factor Authentication (MFA) & Root Account Security
AWS CLI & SDK Setup
03. Compute (EC2)
Launching an EC2 Instance
Security Groups (Firewall Rules)
Private vs. Public IPs & SSH (Key Pairs)
EBS Volumes (Elastic Block Store) & Snapshots
AMIs (Amazon Machine Images)
EC2 Pricing Models (On-Demand, Spot, Reserved)
👑 PRO
04. Storage (S3)
Introduction to S3 (Buckets & Objects)
S3 Storage Classes (Standard, Intelligent-Tiering, Glacier)
Versioning & Lifecycle Policies
S3 Security (Bucket Policies & Encryption)
Static Website Hosting on S3
Storage Gateway & Snow Family (Data Migration)
05. Networking (VPC)
Introduction to VPC (Virtual Private Cloud)
Subnets (Public vs. Private) & CIDR Blocks
Internet Gateway (IGW) & Route Tables
NAT Gateways & Bastion Hosts
VPC Peering & Endpoints
06. High Availability
Elastic Load Balancing (ALB vs. NLB)
Auto Scaling Groups (ASG)
Route 53 (DNS Management & Routing Policies)
07. Databases
RDS (Relational Database Service) Fundamentals
RDS Multi-AZ vs. Read Replicas
Aurora (Serverless & Global)
DynamoDB (NoSQL Key-Value Store)
ElastiCache (Redis & Memcached)
08. Serverless & App Services
Introduction to AWS Lambda
Triggering Lambda from S3/API Gateway
API Gateway (REST & HTTP APIs)
SQS (Simple Queue Service) Decoupling
SNS (Simple Notification Service)
09. Containers & DevOps
Introduction to Docker on AWS
ECS (Elastic Container Service) & Fargate
ECR (Elastic Container Registry)
Infrastructure as Code: CloudFormation Basics
CI/CD on AWS (CodePipeline, CodeBuild, CodeDeploy)
10. Monitoring & Management
CloudWatch (Metrics, Logs, Alarms)
EventBridge (CloudWatch Events)
CloudTrail (Auditing & Governance)
AWS Systems Manager (SSM)
11. Architecture & Cost
The Well-Architected Framework Pillars
AWS Trusted Advisor
AWS Cost Explorer & Budgets
Disaster Recovery Strategies
Back End
Node
Node Essentials Concepts
Node What is
Node Event Loop and non-blocking I/O
Node CommonJS vs ES Modules
Node Global Objects
Node Internal Modules
Node NPM and Dependencies
Node Introduccion Package.json
Node Advance Concepts
Node Streams and Buffers
Node Worker Threads and Child Processes
Node Memory Management and Garbage Collection
Node Clustering
Node Patters Middleware
Node Custom EventEmitters
Node Building Backend Systems
Node Layers Architecture (controllers, services, models)
Node Split Responsabilities
Node Express.js (router, middleware)
Node Database Connection (MongoDB with Mongoose and PostgreSQL with Sequelize/Knex)
Node Authentication and Authorization (JWT, OAuth)
Node Global Error Handling
Node Logging and Catching
Node Logging Practice
👑 PRO
Node Introduction Redis
Node Cache Manual vs Automatic
Node Cache Invalid Strategies
Node Redis Sessions
Node REST APIs
Node Express Routes and Controllers
Node Validation Data with Joi/Yup
Node API Versions
Node Documentation with Swagger/OpenAPI
Node Security: CORS, Rate Limiting, Headers HTTP
GraphQL with Node.js
Node Intro to GraphQL
Schema, Queries, Mutations y Resolvers
Node Apollo Server
Node Data Base Integration
Node Autenticationn in GraphQL
Node Comparative REST
Testing in Node.js
Node Test Types: E2E, Unit, Integration
Node Mocha + Chai / Jest
Node Mocking and spies (with Sinon.js or Jest)
Create Dockerfile for Node.js
Node Intro Docker
Node .Dockerignore use
Node Docker Compose (multi-container apps)
Node Network and Data Persistance
Node Dev Environments and Volumes
Node Deployment Applications
Real Time Chat with WebSockets
SQL
SQL Introduction
Database Concepts
DBMS Overview
Environment Setup
DMBS Tools Usage
First Connections and Steps
SQL Basic Commands
SQL Fundamentals
SELECT
WHERE
ORDER BY
LIMIT
Conditionals and Aggregation Functions
Comparison Operators
AND, OR, NOT
COUNT, SUM, AVG, MIN, MAX
Group By
Having
Data Manipulation Language (DML)
INSERT INTO
UPDATE
DELETE
DROP, COMMIT, ROLLBACK
Management
juniorToMid
Core Technologies Advance-Knowledge
Accessibility Semantic HTML
Advanced CSS
Modern Frameworks and Libraries
Testing
Modern Libraries Frameworks
Optimization and Build
Version Control
Dev Methodologies
Team Work and Communication
Problem solving
Scrum
Introduction to Scrum
Fundamentals of Scrum
Scrum Framework
Roles in Scrum
The Scrum Master
Scrum Events in Detail
Artifacts and Transparency in Scrum
Scaling Scrum
PSM I Certification (Professional Scrum Master I)
Exam Preparation
Practical Application of Scrum
Product Management
01. PM Fundamentals
Introduction to Digital Product Management
Product Lifecycle
Roles in Tech: PM vs Project Manager vs Product Owner
👑 PRO
Key Skills: Soft Skills and Hard Skills
Development Methodologies (Waterfall vs Agile)
02. Discovery
Problem and Opportunity Identification
User Research
Qualitative Interviews and Surveys
Competitive Analysis (Benchmarking)
Creating User Personas
Empathy Maps
03. Product Strategy
Product Vision and Mission Definition
Value Proposition Canvas
Objectives and Key Results (OKRs)
Business Model Canvas & Lean Canvas
Stakeholder Management
04. Definition and Roadmap
Feature Prioritization (RICE, MoSCoW, Kano)
Product Roadmap Creation
MVP Definition (Minimum Viable Product)
Product KPIs and Success Metrics
05. Design and UX
UX/UI Fundamentals for PMs
User Journey Mapping
Wireframing and Prototyping (Low vs High fidelity)
Usability Testing
Collaboration with Designers
06. Technical Execution
Working with Engineering Teams
Writing User Stories
Acceptance Criteria
Backlog Management (Refinement/Grooming)
Scrum Rituals (Sprint Planning, Daily, Retro)
07. Launch and Marketing
Go-to-Market Strategy (GTM)
Positioning and Messaging
Launch Plan (Launch Checklist)
Collaboration with Sales and Marketing
08. Metrics and Growth
Product Analytics (Mixpanel, Google Analytics)
Pirate Metrics (AARRR: Acquisition, Activation, etc.)
Retention and Churn Analysis
A/B Testing and Experimentation
Iteration and Feedback Loops
09. Career and Leadership
Building a Product Portfolio
PM Interview Preparation
Leadership without Authority
Digital Marketing
AI for Digital Marketers
01. AI Foundations
Introduction to AI in Marketing
Generative AI vs. Predictive AI
The AI Marketing Landscape (Tools Overview)
Ethics, Copyright, and Brand Safety
02. Prompt Engineering
Basics of Prompting (Context, Task, Persona)
Zero-shot vs. Few-shot Prompting
Iterative Refinement for Better Outputs
Building a Brand Voice Library
03. Content Marketing
Brainstorming and Ideation with AI
Writing Long-form Blog Posts (SEO-driven)
Repurposing Content (e.g., Blog to LinkedIn)
Editing and Polishing Content
04. Copywriting & Ads
Writing High-Converting Ad Copy (Meta/Google)
Generating Headlines and Hooks
Creating Landing Page Copy
A/B Testing Copy Variations with AI
05. AI for Design & Video
Introduction to AI Image Generators (Midjourney/DALL-E)
Prompting for Specific Visual Styles
AI in Design Tools (Canva Magic Studio, Adobe Firefly)
AI Video Creation (Script-to-Video tools)
AI Voiceovers and Avatars (ElevenLabs, HeyGen)
06. Social Media Strategy
Creating Monthly Content Calendars
Generating Viral Hooks and Captions
Automating Social Interaction (Chatbots)
Trend Analysis with AI
07. SEO & Research
Keyword Research and Clustering with AI
Competitor Analysis and Summarization
Creating User Personas with AI
Generating Schema Markup and Meta Tags
08. Email Marketing
Personalization at Scale
Writing Cold Outreach Emails
Subject Line Optimization
Automated Drip Campaign Structures
09. Data & Analytics
Analyzing Customer Data (ChatGPT Data Analyst)
Sentiment Analysis of Reviews
Predictive Analytics for Marketers (No-Code)
Reporting and Visualization Helpers
10. Workflow & Integration
Building an AI Marketing Stack
Automating Workflows (Zapier/Make + OpenAI)
Future of AI in Marketing
AI Art Direction & Creative Workflows
Fundamentals and Ethics
Design vs AI Direction
AI Legal & Copyright Basics
Intellectual Property EU/USA
AI Bias & Visual Stereotypes
Photography Terms for Prompting
Lighting & Composition Rules
Midjourney v6 Intro
Midjourney Parameters (--s, --w, --no)
Midjourney Aspect Ratios (--ar)
Advanced Prompting Structure
Prompt Layering: Subject + Env + Light
Character Consistency (--cref)
Style Consistency (--sref)
DALL-E 3 Vision & Iteration
Stable Diffusion Concepts
Open Source vs Closed Models
Intro to ControlNet
Pose Guidance & Skeletal Mapping
Sketch to Image
Inpainting Basics
Generative Expand (Outpainting)
Fixing Details: Hands & Eyes
AI Upscaling Tools
Magnific AI Workflow
High Res & Print Quality
Photoshop Generative Fill
Firefly Integration
Illustrator Text to Vector
AI Vector Logos & Icons
The Sandwich Workflow
Human-AI-Human Handoff
Text-to-Video Intro
Runway Gen-2 & Gen-3
Pika Labs Controls
Image-to-Video Animation
AI Lip Sync Tools
Avatars with HeyGen
Sync Labs Integration
Brand Consistency Challenges
👑 PRO
Intro to LoRAs
Training Custom Models
Face Training (Leonardo AI)
Style Training for Brands
LoRA Implementation
Campaign 360 Briefing
AI Visual Identity Setup
AI Product Photography
AI Commercial Spot (15s)
👑 PRO
Final Workflow Defense
👑 PRO

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← Back to Tutorials
Phase 1 Mastery

Three.js Mastery

Build a 3D universe from scratch. Understand the mechanics of WebGL, Scene, Camera, and Renderer to create stunning immersive web experiences.

Total Lessons17
Skill LevelIntermediate

Course Curriculum

Lesson 1

ThreeJS Module 1

Lesson 2

ThreeJS Module 2

Lesson 3

ThreeJS Module 3

Lesson 4

ThreeJS Module 4

Lesson 5

ThreeJS Module 5

Lesson 6

ThreeJS Module 6

Lesson 7

ThreeJS Module 7

Lesson 8

ThreeJS Module 8

Lesson 9

ThreeJS Module 9

Lesson 10

ThreeJS Module 10

Lesson 11

ThreeJS Module 11

Lesson 12

ThreeJS Module 12

Lesson 13

ThreeJS Module 13

Lesson 14

ThreeJS Module 14

Lesson 15

ThreeJS Module 15

Lesson 16

ThreeJS Module 16

Lesson 17

ThreeJS Module 17

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