Masters in Artificial Intelligence & Machine Learning
Total Number of Modules17
Total Number of Topics301
Estimated Duration460:00 H
Module 1 – Python
- Introduction to Python60 Mins
- Practice Program60 Mins
- Python Operators60 Mins
- Practice Program60 Mins
- Control Flow Statement60 Mins
- Practice Program60 Mins
- List60 Mins
- Practice Program60 Mins
- Tuples60 Mins
- Practice Program60 Mins
- Set & Dictionaries90 Mins
- Practice Program60 Mins
- Python Functions120 Mins
- Practice Program90 Mins
- Python Modules90 Mins
- Practice Program90 Mins
- Python OOPs120 Mins
- Practice Program90 Mins
- Python Inheritance120 Mins
- Practice Program90 Mins
- Python Constructor120 Mins
- Practice Program90 Mins
- Python Exception Handling180 Mins
- Practice Program90 Mins
- Python File Handling90 Mins
- Practice Program90 Mins
- List & Dictionary Comprehension180 Mins
- Practice Program90 Mins
- Iterators & Generators180 Mins
- Practice Program90 Mins
- Functional Programming180 Mins
- Practice Program90 Mins
- Lambda Functions (Advanced)180 Mins
- Practice Program180 Mins
- String Processing180 Mins
- Practice Program90 Mins
- File Handling (Advanced)90 Mins
- Practice Program90 Mins
- Multiple Exception Handling90 Mins
- Practice Program90 Mins
- Modules & Packages (Advanced)120 Mins
- Practice Program90 Mins
- Memory & Performance Basics90 Mins
- Practice Program90 Mins
- Working With Input Data120 Mins
- Practice Program90 Mins
- Project Theory - Student Data Analyzer240 Mins
- Project Practical - Student Data Analyzer240 Mins
- Project Theory - Mini Project Presentation240 Mins
- Project Practical - Implementation & Demonstration240 Mins
Module 2 – MySQL
- Database Management: SQL Basics60 Mins
- SQL Queries - Basic60 Mins
- Aggregation Functions and Joins60 Mins
- Having Clause60 Mins
- SQL Database - Create, Drop, Backup60 Mins
- Database Constraints & Datatypes60 Mins
- SQL Keywords and Functions60 Mins
- MySQL SQL Essentials60 Mins
- Join Types60 Mins
- Practice Program - Real-World Data Analysis90 Mins
- Project Theory - SQL Mini Project120 Mins
- Practice Program - Implementation & Demonstration180 Mins
- Project - Python + SQL Analysis120 Mins
- Project - Implementation120 Mins
Module 3 – NumPy for AI & Numerical Computing
- NumPy Introduction60 Mins
- Array Slicing, Copy vs View60 Mins
- Iterating Arrays60 Mins
- Joining Arrays60 Mins
- Splitting & Searching Arrays60 Mins
- Mathematical Operations60 Mins
- Random Module60 Mins
- Array Operations (AI Core)60 Mins
- Filtering & Advanced Indexing60 Mins
- Project - NumPy Mini Project (Data Analyzer)120 Mins
- Project - Implementation240 Mins
Module 4 – Pandas for Data Analysis & AI
- Introduction to Pandas120 Mins
- Core Pandas Data Structures180 Mins
- Creating and Working with DataFrames180 Mins
- Display Settings & Data Cleaning180 Mins
- Data Transformation & Changing Data Types180 Mins
- Data Analysis180 Mins
- Data Filtering & Selection180 Mins
- Groupby & Aggregation (AI Core)180 Mins
- Merging & Combining Data180 Mins
- Project - Pandas Mini Project (Data Analyzer)240 Mins
- Project - Implementation240 Mins
Module 5 – Matplotlib for AI Visualization
- Introduction to Matplotlib60 Mins
- Basic Plots60 Mins
- Advanced Plots60 Mins
- Plot Customization60 Mins
- Special Techniques60 Mins
- Project - Full Data Analysis & Visualization180 Mins
- Project - Implementation & Demonstration180 Mins
- Project - E-Commerce Analyzer / Sales Dashboard180 Mins
Module 6 – Seaborn for AI & Exploratory Data Analysis
- Introduction to Seaborn60 Mins
- Installation and Setup60 Mins
- Categorical Plots60 Mins
- Distribution Plots60 Mins
- Relational Plots60 Mins
- Matrix Plots60 Mins
- Plot Styling and Aesthetics60 Mins
- EDA for AI (Core)60 Mins
- Correlation & Feature Analysis60 Mins
- Project - Real-World Data Visualization120 Mins
Module 7 – Math for AI & ML
- Linear Algebra - Vectors60 Mins
- Matrices (AI Foundation)60 Mins
- Statistics Basics60 Mins
- Probability Basics60 Mins
- Bayes Theorem (Introduction)60 Mins
- Calculus for AI (Light Version)180 Mins
- Project - Math for AI Mini Project180 Mins
- Project - Implementation240 Mins
Module 8 – Machine Learning for AI Engineering
- Introduction to ML & AI Engineering Workflow60 Mins
- Data Preprocessing for Machine Learning60 Mins
- Training & Testing Data Split60 Mins
- Linear Regression90 Mins
- Logistic Regression (Classification)60 Mins
- K-Nearest Neighbors (KNN)60 Mins
- Decision Tree Algorithm60 Mins
- Random Forest60 Mins
- Naive Bayes Classifier60 Mins
- Support Vector Machine (SVM)60 Mins
- Clustering (Unsupervised Learning)60 Mins
- Model Evaluation Metrics60 Mins
- Hyperparameter Tuning60 Mins
- Feature Engineering60 Mins
- Machine Learning Pipelines (AI Engineering Core)60 Mins
- Model Deployment Basics (AI Engineering)60 Mins
- Building Simple ML API60 Mins
- Introduction to Kaggle Datasets60 Mins
- Project - Industry-Level AI Project Design90 Mins
- Project - End-to-End AI System Implementation120 Mins
Module 9 – Deep Learning for AI Engineering
- Introduction to Deep Learning & Neural Networks60 Mins
- Deep Learning Frameworks (Industry Stack)60 Mins
- Neural Network Architecture60 Mins
- Training Neural Networks (Python Basics)60 Mins
- Introduction to TensorFlow & Keras60 Mins
- Convolutional Neural Networks (CNN)60 Mins
- CNN Architectures60 Mins
- Recurrent Neural Network (RNN) - Sequential Data60 Mins
- LSTM & GRU Networks60 Mins
- NLP Fundamentals for AI Engineering60 Mins
- Hugging Face NLP Applications60 Mins
- Attention Mechanism60 Mins
- Transformers Architecture (Modern AI Core)60 Mins
- Pretrained Language Models60 Mins
- Model Optimization in Deep Learning60 Mins
- Evaluation of Deep Learning Models60 Mins
- Transfer Learning (AI Industry Technique)60 Mins
- GenAI & Modern AI Introduction60 Mins
- Project - Deep Learning Mini Project Design90 Mins
- Project - End-to-End Deep Learning Implementation240 Mins
Module 10 – Natural Language Processing (NLP) for AI Engineering
- Introduction to NLP90 Mins
- Text Preprocessing (Core NLP)90 Mins
- Text Representation (Feature Engineering)90 Mins
- Word Embeddings (Modern NLP)90 Mins
- NLP Using Scikit-Learn90 Mins
- Sentiment Analysis90 Mins
- Text Classification Models90 Mins
- Sequence Modeling Introduction90 Mins
- Advanced NLP (Deep Learning Intro)90 Mins
- Attention Mechanism (Modern NLP Core)90 Mins
- Transformers (Modern AI Core NLP)90 Mins
- Hugging Face NLP (Industry Tool)90 Mins
- LLM & Generative NLP Intro90 Mins
- Project - NLP Mini Project Design180 Mins
- Project - End-to-End NLP Implementation180 Mins
Module 11 – Large Language Models (LLM) for AI Engineering
- Introduction to LLMs90 Mins
- Transformers Revision for LLMs90 Mins
- LLM Architecture90 Mins
- Tokenization & Context Handling90 Mins
- Pretraining & Fine-Tuning90 Mins
- LLM Prompt Engineering90 Mins
- Hugging Face LLM Ecosystem90 Mins
- LLM APIs (OpenAI / Gemini / Claude)90 Mins
- Fine-Tuning Basics (AI Engineer Level)90 Mins
- RAG (Retrieval Augmented Generation)90 Mins
- Vector Databases90 Mins
- LLM Evaluation90 Mins
- LLM Optimization180 Mins
- LLM Application Building90 Mins
- Project - LLM Project Design180 Mins
- Project - End-to-End LLM Project180 Mins
Module 12 – MLOps for AI Engineering (Production AI Systems)
- Introduction to MLOps90 Mins
- ML System Architecture90 Mins
- Model Versioning90 Mins
- Experiment Tracking (MLflow)90 Mins
- Model Saving & Loading90 Mins
- Data Pipelines90 Mins
- ML Pipelines (Scikit-Learn + Automation)90 Mins
- Model Deployment (Core)90 Mins
- Docker for AI Engineering90 Mins
- Cloud Deployment Basics90 Mins
- CI/CD for Machine Learning90 Mins
- Model Monitoring90 Mins
- Observability in AI Systems90 Mins
- Feature Stores90 Mins
- Real-Time ML Systems90 Mins
- LLM MLOps (Modern AI)90 Mins
- Automated ML System (Auto-MLOps)90 Mins
- Project - MLOps Project Design90 Mins
- Project - End-to-End MLOps Implementation180 Mins
Module 13 – Computer Vision for AI Engineering
- Introduction to Computer Vision90 Mins
- OpenCV Basics90 Mins
- Image Processing Fundamentals90 Mins
- Feature Extraction in Images90 Mins
- CNN for Image Classification90 Mins
- Transfer Learning in CV90 Mins
- Image Augmentation90 Mins
- Object Detection Introduction90 Mins
- Advanced Object Detection90 Mins
- Face Detection90 Mins
- Face Recognition System90 Mins
- Image Segmentation90 Mins
- Vision Transformers (ViT) - Modern AI90 Mins
- Real-Time Computer Vision Systems90 Mins
- Model Optimization in CV90 Mins
- Deployment of CV Models90 Mins
- CV + LLM Integration (Modern AI)90 Mins
- Project - Computer Vision Project Design90 Mins
- Project - End-to-End Computer Vision Project180 Mins
Module 14 – History and Future of AI
- Introduction to Artificial Intelligence90 Mins
- History of AI (AI Evolution)90 Mins
- AI Milestones & Breakthroughs90 Mins
- AI Industry Transformation90 Mins
- Why AI is Important Today90 Mins
- Future of AI (Next 10-20 Years)90 Mins
- Future Technologies in AI90 Mins
- GenAI Era & Future Models90 Mins
- Ethics & Risks in Future AI90 Mins
- AI Career Roadmap (Future Skills)90 Mins
Module 15 – Agentic AI
- Types of AI Agents90 Mins
- Components of Agentic Systems90 Mins
- Single Agent Systems90 Mins
- Multi-Agent Systems90 Mins
- Agent Communication Protocols60 Mins
- Reasoning in Agents - Planning Strategies90 Mins
- Memory in Agentic AI90 Mins
- Tool Calling in Agents90 Mins
- Retrieval Augmented Agents60 Mins
- Autonomous Workflows60 Mins
- Agent Planning & Execution90 Mins
- Multi-Step Reasoning Agents90 Mins
- Frameworks for Agentic AI90 Mins
- Introduction to MCP (Model Context Protocol)90 Mins
- MCP Architecture90 Mins
- MCP Setup90 Mins
- MCP With Agentic AI90 Mins
- Enterprise MCP Systems90 Mins
- RAG Agents90 Mins
- AI Agent Security90 Mins
- Monitoring Agentic Systems60 Mins
- Enterprise Agentic AI60 Mins
- Future of Agentic AI90 Mins
Module 16 – Final Capstone Project
- End-to-End AI System Design & Phase Explanation240 Mins
- End-to-End AI System Implementation180 Mins
Module 17 – Prompt Engineering
- Fundamentals of Prompt Engineering60 Mins
- Role of Prompt Engineer60 Mins
- Prompt Engineering Workflow60 Mins
- Instruction & Context60 Mins
- Input Data & Output Format60 Mins
- Constraints, Delimiters & Prompt Roles60 Mins
- Zero-shot & One-shot Prompting60 Mins
- Few-shot & Role-based Prompting60 Mins
- Persona, Task-based & Q&A Prompting60 Mins
- Clarity, Specificity & Completeness60 Mins
- Ambiguity Control, Verbosity & Tone/Domain Control60 Mins
- Instruction Prompting & Contextual Prompting60 Mins
- Clarity, Specificity & Completeness (Advanced)60 Mins
- Prompt Chaining & Re-Prompting Strategies60 Mins
- Chain-of-Thought (CoT) Prompting60 Mins
- Tree-of-Thought & Self-Consistency Prompting60 Mins
- Step-by-Step & Decomposition Prompting60 Mins
- Length & Format Control60 Mins
- Structured Output Formats60 Mins
- Style & Code Output Control60 Mins
- Prompt Templates & Parameters60 Mins
- Prompt Libraries & Documentation60 Mins
- Quality Evaluation Metrics60 Mins
- Bias, Testing & Error Analysis60 Mins
- Bias & Hallucination Control60 Mins
- Privacy, Copyright & Guardrails60 Mins
- Content & Writing Domain60 Mins
- Programming Domain60 Mins
- Data & Analytics Domain60 Mins
- Education Domain60 Mins
- Domain Prompt Integration60 Mins
- Mini Domain Project60 Mins
- Memory & Workflow Prompts60 Mins
- Agent & Tool Prompts60 Mins
- Function & Multi-Agent Prompting60 Mins
- Chat Models60 Mins
- Developer Platforms60 Mins
- Vision-Based Prompting60 Mins
- Audio & Diagram Prompting60 Mins
- Regulated Industries60 Mins
- Business Industries60 Mins
- Portfolio & Freelancing60 Mins
- Job Preparation60 Mins
- Project Development60 Mins
- Presentation & Evaluation60 Mins