Module 1: Python for AI/ML

Python Programming

• Introduction to Python Programming
• Variables, Data Types & Operators
• Data Structures
• Functions
• Conditional Flow Statements
• Lambda, Map, Filter Functions
• Error Handling

Python for Data Science

• Mathematical Computing using NumPy
• Creating 1d, 2d and 3d Arrays
• Accessing Array Elements
• Indexing, Slicing, Iteration
• Data Analysis using Pandas
• Understanding Pandas
• Series & DataFrames
• DataFrame Operations
• Filtering, Grouping and Joining
• Loading Data from Datasets to DataFrames
• Data Visualization using Matplotlib
• Different Types of Plots & Charts

Module 2: Statistics & EDA

• Introduction to Descriptive Statistics
• Data & Variables in Statistics
• Measures of Central Tendency (Mean, Median & Mode)
• Variance & Standard Deviation
• Univariate Analysis (Histograms, Box Plots & Bar Charts)
• Bivariate/Multivariate Analysis (Line Plots, Scatter Plots, Heat Maps)
• Probability Distribution & Central Limit Theorem
• Hypothesis Testing & Inferential Statistics

Module 3: Introduction to Machine Learning

• Types of Machine Learning
• Steps to Build an ML Model
• Supervised ML vs Unsupervised ML
• Supervised Learning: Regression & Classification
• Unsupervised Learning: Clustering
• Linear Regression: Simple & Multiple
• Gradient Descent
• Logistic Regression
• Decision Trees & Random Forest
• KNN Algorithm
• K-Means Clustering
• Regression Metrics
• Classification Metrics
• Overfitting & Underfitting
• Bagging (Ensemble Methods)
• Boosting (AdaBoost, XGBoost, Gradient Boosting & Stacking)
• Feature Engineering
• Model Tuning & Performance Optimization
• Optimization Techniques to Improve ML Models

Module 4: Deep Learning & NLP

• Introduction to Neural Networks
• Types of Neural Networks
• Computer Vision
• Natural Language Processing (NLP)

Module 5: Artificial Intelligence & Generative AI

• Introduction to Artificial Intelligence
• History of AI
• Types of AI
• Areas and Related Disciplines of AI
• Understanding AI Subdomains
• Applications of AI
• Tasks AI Can Solve
• Introduction to Generative AI
• Evolution of Gen AI
• Gen AI vs Traditional ML
• How Gen AI Works
• Applications of Gen AI
• Popular Gen AI Tools
• Introduction to ChatGPT
• Large Language Models (LLM)
• Developing Gen AI Models: Transformers
• Prompt Engineering
• Building Gen AI Models on Azure

Module 6: Azure AI Engineer Associate

• Getting Started with Azure AI Services
• Azure Machine Learning Studio & Workspace
• Design a Machine Learning Solution with Azure ML Studio
• Model Deployment with Azure ML
• Create Computer Vision Solutions with Azure AI Vision
• Develop NLP Solutions with Azure AI Services
• Develop Solutions with Azure AI Document Intelligence

Module 7: Generative AI using Azure OpenAI Service

• Introduction to Azure OpenAI Service
• Building NLP Solutions using Azure OpenAI Service
• Apply Prompt Engineering with Azure OpenAI Service
• Generate Code with Azure OpenAI Service
• Implement RAG with Azure OpenAI Service
• Generate Images using DALL-E