Unit 1: What is AI?
Unit 2: Types of AI
Unit 3: AI in the Real World
Unit 4: AI Engineering
Intro to AI for Aspiring AI Engineers
A comprehensive introduction to Artificial Intelligence, Machine Learning, and Deep Learning, designed to equip aspiring AI Engineers with the foundational knowledge and practical skills needed to build responsible and effective AI solutions.
Unit 1: Understanding Machine Learning Fundamentals
Unit 2: Types of Machine Learning
Unit 3: Reinforcement Learning and Algorithms
Unit 1: Deep Learning Fundamentals
Unit 2: Types of Neural Networks
Unit 3: Training Deep Learning Models
Unit 1: The Importance of Data
Unit 2: Data Collection Methods
Unit 3: Data Cleaning Techniques
Unit 4: Data Transformation Techniques
Unit 5: Advanced Data Handling
Unit 1: Understanding Feature Engineering
Unit 2: Feature Selection Techniques
Unit 3: Feature Creation and Transformation
Unit 4: The Role of Domain Knowledge
Unit 1: Model Selection Fundamentals
Unit 2: Model Training Essentials
Unit 3: Hyperparameter Tuning and Cross-Validation
Unit 1: Why Evaluate Models?
Unit 2: Evaluation Metrics
Unit 3: Overfitting and Underfitting
Unit 4: Techniques to Improve Models
Unit 5: Validating on Unseen Data
Unit 1: Understanding the AI Project Lifecycle
Unit 2: Model Building and Deployment
Unit 3: Collaboration, Communication, and Challenges
Unit 1: Understanding AI Bias
Unit 2: Ethical Implications of AI
Unit 3: Mitigating Bias and Responsible AI
Unit 1: Deployment Strategies
Unit 2: Integration and Monitoring
Unit 3: Model Drift and Maintenance