Advanced Generative AI Certification Course

• Overview of Artificial Intelligence
• Traditional AI vs. Generative AI
• Evolution of AI models (Rule-Based → ML → DL → Generative AI)
• Industry Use Cases

Python Basics 9 hours

• Variables, Data Types, Control Flow, Loops, Functions
• List, Dictionary, Tuple, Set Operations

Python NumPy & Pandas 9 hours

• NumPy Arrays & Operations
• Pandas DataFrames, Data Cleaning, GroupBy & Aggregations

Exploratory Data Analysis (EDA) 6 hours

• Descriptive Statistics, Missing Values, Outlier Detection
• Data Visualization for EDA

SQL for Data Analytics 6 hours

• Basic Queries: SELECT, WHERE, GROUP BY, HAVING, JOINS
• Window Functions & Analytical Queries

Data Visualization with Python 4 hours

• Matplotlib, Seaborn, Plotly Basics

Visual Storytelling using Power BI 6 hours

• Creating Dashboards, Filtering & Interactions

Fundamentals of Linear Algebra 6 hours

• Vectors, Matrices, Eigenvalues & Eigenvectors
• Dot Product, Matrix Operations, Applications in AI

Probability & Statistics 4 hours

• Descriptive Statistics (Mean, Median, Mode, Variance, Standard Deviation)
• Probability Distributions: Normal, Bernoulli, Binomial
• Central Limit Theorem

Reinforcement Learning

• Train agents using policy and value-based methods to understand environmental interactions.

Supervised Learning 6 hours

• Regression: Linear & Logistic Regression
• Classification: Decision Trees, Random Forest, SVM
• Model Evaluation: Accuracy, Precision, Recall, ROC-AUC

Unsupervised Learning 4 hours

• Clustering: K-Means, Hierarchical Clustering
• Dimensionality Reduction: PCA, t-SNE

Neural Networks 6 hours

• Perceptron, Activation Functions, Backpropagation
• Multi-Layer Perceptrons (MLPs)

Convolutional Neural Networks (CNNs) 6 hours

• Image Classification, CNN Architectures (VGG, ResNet)

Recurrent Neural Networks (RNNs) & LSTMs 6 hours

• Sequential Data, Text Processing

Natural Language Processing (NLP) for GenAI 7 hours

• Introduction to NLP, Libraries and tools for NLP
• Text Cleaning in sequential data
• Text Processing Methods – BOW, TF-IDF, N-Grams
• Word Embeddings – Word2Vec

Introduction to Generative AI

• What is Generative AI? Evolution from Rule-Based AI to GenAI
• Differences: Generative AI vs. Traditional AI
• Industry Applications:
  1. Content Creation (Chatbots, Story Writing, Blogging)
  2. Code Generation (AI-Assisted Programming)
  3. . Image & Video Synthesis (DALL·E, MidJourney, DeepSeek Vision)

Prompt Engineering & Optimization

• Fundamentals of Prompt Engineering
  1. Zero-shot, Few-shot, Chain-of-Thought (CoT) Prompting
  2. Role-based Prompts, Multi-turn Conversations
• Advanced Prompting Techniques
  1. System vs. User Prompts, Style Transfer, Iterative Prompting

Encoder-Decoder Architectures & Attention Mechanism

• Understanding Sequence-to-Sequence (Seq2Seq) Models
• Introduction to Attention Mechanisms
  1. Self-Attention & Cross-Attention
  2. Scaled Dot-Product Attention & Multi-Head Attention
• Transformers & Evolution
  1. Introduction to Transformers (Vaswani et al., 2017)
  2. Positional Encoding & Feed-Forward Networks

Foundation of Generative Models

• Types of Generative Models
  1. Variational Autoencoders (VAEs)
  2. Generative Adversarial Networks (GANs) – StyleGAN, CycleGAN
  3. Transformer-Based Models (GPT, BERT, T5)
• Understanding AI Hallucinations, Bias, and Model Safety
  1. Variational Autoencoders (VAEs)
  2. Generative Adversarial Networks (GANs) – StyleGAN, CycleGAN
  3. Transformer-Based Models (GPT, BERT, T5)

Large Language Models (LLMs) & Fine-Tuning

• Popular LLMs: GPT-4, DeepSeek, LLaMA, Mistral, Claude, Falcon
• Fine-Tuning vs. Pre-training of LLMs
  1. Transfer Learning for LLMs
  2. Customizing LLMs for Domain-Specific Use Cases

Retrieval-Augmented Generation (RAG)

• Why RAG? Understanding LLM Limitations
• RAG Pipeline Components:
  1. Document Embeddings & Vector Databases (Pinecone, ChromaDB)
  2. Query Processing & Context Retrieval

Foundation of Generative Models

• Implementing RAG with Hugging Face & LangChain
• What is LlamaIndex?
• Using LlamaIndex for Efficient Document Retrieval

Multimodal AI – Text, Image, Video & Speech Processing

• Text-to-Image & Image-to-Image Generation
  1. How DALL·E, MidJourney, and Stable Diffusion Work
  2. Latent Diffusion Models (LDMs) & Hugging Face Implementations
• Speech-to-Text & AI Voice Processing
  1. Whisper, Wav2Vec, DeepSeek-STT, Real-Time Speech Transcription
• Advanced Multimodal Models
  1. OpenAI GPT-4V, Gemini
  2. Text-to-Image, Image Captioning

Agentic AI & Autonomous AI Agents

• What is Agentic AI?
  1. Understanding Autonomous AI Systems
• AI Agent Frameworks:
  1. LangChain, AutoGPT, Hugging Face Agents
  2. Building AI Agents for Research, Trading, and Business Automation

Hugging Face Ecosystem

• Hugging Face Models, Spaces, and Transformers
• Fine-Tuning LLMs & Custom AI Deployments
• Enterprise Use Cases
  1. AI Chatbots, Code Generation, AI for Research

Real-Time Generative AI in Business Applications

• Generative AI in Healthcare
  1. AI-Powered Drug Discovery, Medical Imaging
• AI in Finance
  1. Synthetic Data for Risk Modeling & Fraud Detection
• Automating Business Processes with AI

Ethics, AI Governance & Future Trends

• Responsible AI & AI Governance
  1. EU AI Act, OpenAI’s AI Policy
• The Future of Generative AI
  1. AI-Powered Autonomous Systems
  2. Trends in AGI (Artificial General Intelligence)