AI/ML Explorer Minidegree
1
AI/MLOps Mission 1 : Build Machine Learning Foundations
100 AI XPsMachine Learning Foundations:
- Supervised and Unsupervised Learning
- Reinforced Learning
- Feature Engineering and Dataset Splitting
- Training vs Inference
- Model Evaluation Metrics
- Hyperparameter Tuning and Bias/Variance
9 Steps
- Lesson : Traditional Programming vs Machine Learning
- Lesson : Supervised Learning
- Lesson: Unsupervised Learning
- Lesson: Reinforcement Learning
- Lesson: Feature Engineering and Dataset Splitting
- Lesson: Training vs Inference
- Lesson : How fit is your Model ? Evaluation and Over/Underfitting
- Lesson : Hyperparameter Tuning and Bias/Variance
- Quiz – Building Blocks of Machine Learning
2
AI/MLOps Mission 2 – Learn LLM Concepts
100 AI XPsLLMs:
- LLLM Concepts, Tokens Parameters
- Transformers and Attention Mechanism
- Pre-Training vs Fine Tuning
- Prompt Engineering
- Retrieval Augmented Generation (RAG)
3
AI/MLOps Mission 3 – Learn the Basics of Agentic AI
100 AI XPsAgentic AI
- Goals and Tools
- Memory and Planning
- Agent Architecture and Types of Agents
- Agentic DevOps and MLOps
