- Introduction to Python and AI/ML
- Data Types, Data Structures , and Control Flow
- Functions and Modules
- File Handling, NumPy for Numerical Operations and Introduction to Arrays and Matrices
- List Comprehensions, Lambda Functions and Decorators
- Pandas, Data Frames and Data Manipulation using Pandas
- Exploratory Data Analysis (EDA) with Pandas
- Basics of Machine Learning & Scikit-Learn Library
- Model Training and Evaluation + Supervised Learning with Scikit-Learn
- Introduction to Artificial Intelligence(AI)
- Introduction to Deep Learning and Neural Networks
- Introduction to AI and ML
- Introduction to Statistics and Math
- Data Preprocessing
- Supervised Learning
- Unsupervised Learning
- Introduction to Machine Learning Algorithms
- Neural Networks Basics
- Deep Learning Frameworks
- Convolutional Neural Networks (CNN)
- Natural Language Processing (NLP)
- Image Processing/ Computer Vision
- Reinforcement Learning
- Model Deployment
- Advanced Topics
- Teacher: AI Trainer
- Introduction to Prompt Engineering and Generative AI
- Understanding Generative AI
- The Significance of Prompt Engineering
- Historical Content and Evolution of Language Models
- Foundations of Prompt Engineering
- The Mechanics of Language Models
- Crafting Effective Prompts
- Evaluation AI Responses and Iterative Refinement
- Beyond Basics: Complex Prompt Applications
- Optimizing Prompts for Specific Outcomes
- Interactive Applications with AI
