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Front End

HTML

HTML First Document

HTML Basic Structure

HTML Code in the HTML Browser

HTML Tags and Attributes

HTML Common Tags: <div>, <span>, <h1>-<h6>, <p>, <br>, <hr>

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 Creating Links <a>

HTML Link Attributes: href and target

HTML Internal and External Links

HTML Email Links in HTML (mailto:)

HTML Creating a Table (<table>, <tr>, <td>, <th>)

HTML Table Attributes: border, cellpadding, cellspacing

HTML Creating Table Headers and Merged Cells

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 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 Incorporation

CSS Basic Selectors

CSS Fonts and Text

CSS Text Alignment

CSS Background Properties

CSS Background Image

CSS Width and Height

CSS Margin and Padding

CSS Positioning

CSS Flexbox Intro

CSS Flexbox Container

CSS Flex Direction

CSS Justify Content

CSS Align Items

CSS Flexbox Items

CSS Display Grid

CSS Grid Columns

CSS Relative Units

CSS Media Queries

CSS Responsive Design

CSS Transitions and Animations

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 Introduction Jsx

React First Steps

React Structure

React Components, Props, State

Difference Function vs Class

React Components

React Functional Components

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 Forms and state Management inputs

React useEffect

React useContext

React useReducer

React Custom Hooks

Eventos common: onClick, onChange, onSubmit, etc.

Eventos sintéticos React

React PreventDefault

React Conditional Rendering and Lists

React Conditional Render

React key in List

React CSS Style

React inline and Class Styles

React CSS Modules

React Dynamic Style

React Style Libraries

React-router-dom

React Dynamic Routes

React Route, Switch, y Link

React useHistory

React Store, Actions, Reducers

React Redux Hooks

React HttpAxios

React LazySuspense

React Condicional vs Lazy vs Suspense

React React.memo y useMemo

Angular

Angular Introduction

Angular Architecture

Create Angular Project

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

Angular Modules (NgModules)

Standalone Components

Advanced Dependency Injection

Component Lifecycle Mastery

Testing Foundations

Component Testing Mastery

Service & Logic Testing

Launch: Deploy & Optimize

Vue

Setup & The App Instance

Reactivity: ref vs reactive

Computed Properties

Methods & Event Handling

Two-Way Binding (v-model)

Conditional Rendering

Lifecycle Hooks

Components & Props

Provide / Inject

Vue Router Intro

Three

Introduction to WebGL & Three.js

Creating a Scene

Cameras & Perspectives

The WebGL Renderer

Meshes & Transformations

Textures & Mapping

The Animation Loop

Particles & Sprites

Importing 3D Models

Raycaster & Interaction

Physics Integration

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)

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

Capstone Project: Development of Complete AI Web Application

Capstone Project: Presentation and Functional Demo

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)

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

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

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

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

Pandas

Introduction to Pandas

Pandas Getting Started

01. Core Data Structures

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

06. Visualization

Pandas Plotting Data

Pandas Advanced Charts

Final Pandas Analytics Challenge

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

03. Spatial Data & Statistics

SciPy Spatial Data

SciPy Matlab Arrays

SciPy Interpolation

SciPy Significance Tests

Final SciPy Challenge

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

Custom Layers and Models

03. Training Fundamentals

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

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

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)

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 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

Node Introduction Redis

Node Cache Manual vs Automatic

Node Cache Invalid Strategies

Node Redis Sessions

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

Environment Setup

DMBS Tools Usage

First Connections and Steps

SQL Basic Commands

SQL Fundamentals

Conditionals and Aggregation Functions

Comparison Operators

COUNT, SUM, AVG, MIN, MAX

Data Manipulation Language (DML)

DROP, COMMIT, ROLLBACK

Management

juniorToMid

Core Technologies Advance-Knowledge

Accessibility Semantic HTML

Modern Frameworks and Libraries

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

The Scrum Master

Scrum Events in Detail

Artifacts and Transparency in 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

Key Skills: Soft Skills and Hard Skills

Development Methodologies (Waterfall vs Agile)

02. Discovery

Problem and Opportunity Identification

Qualitative Interviews and Surveys

Competitive Analysis (Benchmarking)

Creating User Personas

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

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)

Final Workflow Defense

Quick References

Technical Resources

Insights

Community

Code Syllabus

Courses Catalog

Front End

HTML

HTML First Document

HTML Basic Structure

HTML Code in the HTML Browser

HTML Tags and Attributes

HTML Common Tags: <div>, <span>, <h1>-<h6>, <p>, <br>, <hr>

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 Creating Links <a>

HTML Link Attributes: href and target

HTML Internal and External Links

HTML Email Links in HTML (mailto:)

HTML Creating a Table (<table>, <tr>, <td>, <th>)

HTML Table Attributes: border, cellpadding, cellspacing

HTML Creating Table Headers and Merged Cells

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 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 Incorporation

CSS Basic Selectors

CSS Fonts and Text

CSS Text Alignment

CSS Background Properties

CSS Background Image

CSS Width and Height

CSS Margin and Padding

CSS Positioning

CSS Flexbox Intro

CSS Flexbox Container

CSS Flex Direction

CSS Justify Content

CSS Align Items

CSS Flexbox Items

CSS Display Grid

CSS Grid Columns

CSS Relative Units

CSS Media Queries

CSS Responsive Design

CSS Transitions and Animations

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 Introduction Jsx

React First Steps

React Structure

React Components, Props, State

Difference Function vs Class

React Components

React Functional Components

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 Forms and state Management inputs

React useEffect

React useContext

React useReducer

React Custom Hooks

Eventos common: onClick, onChange, onSubmit, etc.

Eventos sintéticos React

React PreventDefault

React Conditional Rendering and Lists

React Conditional Render

React key in List

React CSS Style

React inline and Class Styles

React CSS Modules

React Dynamic Style

React Style Libraries

React-router-dom

React Dynamic Routes

React Route, Switch, y Link

React useHistory

React Store, Actions, Reducers

React Redux Hooks

React HttpAxios

React LazySuspense

React Condicional vs Lazy vs Suspense

React React.memo y useMemo

Angular

Angular Introduction

Angular Architecture

Create Angular Project

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

Angular Modules (NgModules)

Standalone Components

Advanced Dependency Injection

Component Lifecycle Mastery

Testing Foundations

Component Testing Mastery

Service & Logic Testing

Launch: Deploy & Optimize

Vue

Setup & The App Instance

Reactivity: ref vs reactive

Computed Properties

Methods & Event Handling

Two-Way Binding (v-model)

Conditional Rendering

Lifecycle Hooks

Components & Props

Provide / Inject

Vue Router Intro

Three

Introduction to WebGL & Three.js

Creating a Scene

Cameras & Perspectives

The WebGL Renderer

Meshes & Transformations

Textures & Mapping

The Animation Loop

Particles & Sprites

Importing 3D Models

Raycaster & Interaction

Physics Integration

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)

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

Capstone Project: Development of Complete AI Web Application

Capstone Project: Presentation and Functional Demo

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)

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

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

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

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

Pandas

Introduction to Pandas

Pandas Getting Started

01. Core Data Structures

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

06. Visualization

Pandas Plotting Data

Pandas Advanced Charts

Final Pandas Analytics Challenge

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

03. Spatial Data & Statistics

SciPy Spatial Data

SciPy Matlab Arrays

SciPy Interpolation

SciPy Significance Tests

Final SciPy Challenge

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

Custom Layers and Models

03. Training Fundamentals

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

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

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)

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 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

Node Introduction Redis

Node Cache Manual vs Automatic

Node Cache Invalid Strategies

Node Redis Sessions

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

Environment Setup

DMBS Tools Usage

First Connections and Steps

SQL Basic Commands

SQL Fundamentals

Conditionals and Aggregation Functions

Comparison Operators

COUNT, SUM, AVG, MIN, MAX

Data Manipulation Language (DML)

DROP, COMMIT, ROLLBACK

Management

juniorToMid

Core Technologies Advance-Knowledge

Accessibility Semantic HTML

Modern Frameworks and Libraries

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

The Scrum Master

Scrum Events in Detail

Artifacts and Transparency in 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

Key Skills: Soft Skills and Hard Skills

Development Methodologies (Waterfall vs Agile)

02. Discovery

Problem and Opportunity Identification

Qualitative Interviews and Surveys

Competitive Analysis (Benchmarking)

Creating User Personas

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

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)

Final Workflow Defense

Quick References

Technical Resources

Insights

Community

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