Certificate Program Details
This course is designed in such a way not disrupt the learners’ work schedule and they can comfortably attend the online sessions and complete the study as well as practice projects.
Curriculum - Foundation
Introduction to AI
- Concepts of Data Science
- Algorithms, Models and Training
- Supervised and Unsupervised Learning
Algorithms and Mathematical Models
- Regression Techniques
- Classification Techniques
- Clustering Techniques
- Time Series Analysis
Study of Data Science Use Cases
- Sentiment Analysis
- Clustering
- Fraud Detection
- Time Series Analysis
- Anomaly Detection
Project on AI Solution for Business Case
- Data Acquisition, Analysis and Management
- Process Analysis, define outcomes and benefits
- Solution Design
Natural Language Processing
- NLP Concepts - Language Pre-processing, Tokens, Embeddings
- Create your own Large Language Model for Question Answering
Neural Networks and Use Cases
- Image Processing
- NLP - Question Answering
Introduction to Generative AI
- Large Language Models
- LLM APIs
- Programmatic LLM
- Prompts and Prompt Engineering
Study of Gen AI Business Use Cases
- Retrieval Augmented Generation
- Customer Service
- Analytics
- Language Vectors and Vector Databases
Project on AI Solution for Use Case
- Data Acquisition, Analysis and Management
- Process Analysis, define outcomes and benefits
- Solution Design
Ethics and Bias
- Ethics and Bias challenges, Deepfakes
- Sustainability angles of AI / Gen AI
- Model Hallucination
Capstone Project
Curriculum - Advanced
Recap
- Recap of AI Concepts and use cases
- Recap of Gen AI Concepts and use cases
- Prompt Engineering - Advanced
Multi-modal Gen AI
- Generating between Image, Text, Video, Sound
- Gemini, Llama, Stable Diffusion, Midjourney
- Llama, Gemini, Anthropic
AZURE AI Studio
- No-code AI Prototype Development using AZURE Cloud
- 3 Hands-on Example demo cases: Regression, Classification, Clustering
- Learner Project
AZURE Generative AI Studio
- 2 Hands on Demo Examples: RAG - Retrieval Augmented Generation
- Learner Project
Transformation Roadmaps & Capability
- Research on Best Practices and Competitor Analysis
- Identify Organization Goals and appetite
- Maturity Assessment
- Capability Planning
- Use cases Identification
Managing AI / Gen AI Transformation
- Product Ownership of AI and Gen AI Products
- Working with Technology Teams
- Solution Testing Parameters
Ethics, Bias, Regulatory and Privacy Aspects
- Ethical and Bias Considerations in AI and Gen AI solutions
- AI Regulations
- Data Privacy in AI
- How to de-bias your solutions
- AI Guardrails
