AI Engineering (Batch-05)

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Course Content

Introductory Class

  • AI Engineering (Batch-05) – Introductory Session
    02:38:51

Class 01 – Python Fundamentals: Installation & Configuration | Exploring Jupyter Notebook & VS Code | Python Data Types – Integers & Strings | Built-in Functions | String Indexing & Slicing

Class 02 – Python Fundamentals: Python Data Types – Lists, Tuples, Sets & Dictionaries | Essential Built-in Functions | Comparison & Chained Comparison Operators | Conditional Statements (if, elif, else) | User Input Handling | For Loops

Class 03 – Python Fundamentals: Functions – User-Defined Functions | Making Simple Apps: Hangman | Rock Paper Scissors | Multiplication Table Generator | Budget Tracker | And much more using only Python fundamentals!

Class 04 – Python Real-World Applications: Projects: QR Code Generator | Nearby Location Finder | Dynamic Email Sender | Audio Transcription & Translation | Web Scraper

Class 05 – Python Real-World Applications: PDF Tools – Reading, Text & Image Extraction | Merging | Watermarking | Exploring Libraries – Pandas | Importing & Exporting CSV and Excel Files | Built-in Functions of Pandas | Why Pandas is Important for Data Analysis | Case Study (Part 1): EDA – 365 Men Clothing Store

Class 06 – Exploring Libraries: Pandas – Case Study (Part 2): EDA – 365 Men Clothing Store | GroupBy Operations | Filters | Merging DataFrames

Class 07 – Exploring Libraries: Auto EDA – YData Profiling | Sweetviz | D-Tale | Introduction to NumPy | Creating 1D, 2D & 3D Arrays | NumPy Built-in Functions | Array Operations & Practical Examples

Class 08 – Generative AI Fundamentals: What is Generative AI? | How LLMs Work (Basic Intuition) | Exploring ChatGPT & OpenAI | GROQ API | DeepSeek API | Understanding Tokens (Input & Output Tokens) | Model Parameters & Temperature | Practical API Demonstration

Class 09 – Generative AI – Prompt Engineering: What is Prompt Engineering? | Zero-Shot Prompting | One-Shot Prompting | Few-Shot Prompting | Chain of Thought (CoT) | Self-Consistency | ReAct Framework | Structured Prompt Design | Practical Hands-On Examples

Class 10 – Generative AI – LangChain Framework (Part 1): What is LangChain? | LangChain Architecture Overview | Models / LLM Integration | Prompt Templates | Output Parsers | Chains | LCEL (LangChain Expression Language) | Step-by-Step Implementation

Class 11 – Generative AI – LangChain Framework (Part 2): LangChain Memory | Types of Memory: Chat History | Conversation Buffer | Sliding Window Memory | Summary Memory | Practical Implementation | What is RAG? | RAG Architecture Understanding

Class 12 – Generative AI – Real-World Use Cases: Project 01: Marketing Campaign & LinkedIn Job Post Generator using GROQ API | Project 02: DeepSeek Conversational Chatbot | API Integration | Prompt Optimization

Class 13 – Generative AI – Hugging Face: What is Hugging Face? | Hugging Face Ecosystem Overview (Models, Datasets, Spaces) | What is Inference? | Inference vs Model Download (Local Deployment) | Using Hugging Face Inference API | Hands-On Demo with Meta LLaMA Models & Text-to-Image Generation | Course Recap & Student Experience Discussion

Class 14

Class 15

Class 16

Class 17