Course Modules

• Module 1: Introduction to AI/ML
• Module 1.1: AI/ML Scenario based Use Cases
• Module 1.2: AI/ML Process/ Architecture
• Module 1.3: AI/ML Algorithms
• Module 1.4: Model Evaluation
• Module 1.5: AI/ML Deployments
• Module 1.6: Hands on Project: Real World End to End AI/ML Project
• Module 2: Gen AI
• Module 2.1: Introduction to Gen AI
• Module 2.2: Transformers, BERT and GPTs
• Module 2.3: ChatGPT, LAMA & Google PALM
• Module 2.4: Prompt Engineering
• Resource Material: Prompt Engineering Cheatsheet
• Module 2.5: Introduction to Google Gemini
• Module 2.6:Introduction to Stable Difusion
• Module 2.7: Introduction to DALLE & MidJourney
• Module 2.8: Various Open Source GPT Models & Hugging Face
• Module 2.9: Hands on
• Module 3: Custom Models
• Module 3.1: Introduction to Custom Models
• Module 3.2: Real World Use Cases of Custom Models
• Module 3.3: Utilizing Open AI and Google Libraries and Keys
• Module 3.4: Project Work: Develop Real World Custom Gen AI App using Open AI and Google Libraries and Keys
• Module 4: Langchain
• Module 4.1: Introduction to Langchain Framework
• Module 4.2: Vector Databases
• Module 4.3: Chrome DB/ PineCode/ Fassi
• Module 4.4: Project Work: Develop Real World Custom Apps Using Langchain
• Module 5: AI Development Tools
• Module 5.1 : AI Development Tools
• Module 5.2 : Learn Azure Cloud Fundamentals & Azure AI Studio
• Module 5.3 : Google AI Studio
• Module 5.4 : Introduction AWS Sagemaker & Bedrock
• Module 6: Ethical Considerations of GenAI
• Module 7: Future Trends
• Module 8: Project Work: Real World Project Implementation
• Module 9: Resume & Interview Preperation