FUNDAMENTALS OF ARTIFICIAL INTELLIGENCE & MACHINE LEARNING
Unlock the Power of AI & ML for Future-Ready Skills
Course Schedule
| Venue (InHouse) | Fees |
|---|---|
| At Your Organization Premises | Ask For The Quotation |
Course Introduction
This course introduces participants to the core concepts and practical foundations of Artificial Intelligence (AI) and Machine Learning (ML). Designed for professionals with little to no prior background, it provides an intuitive and hands-on understanding of how machines learn from data, how AI is transforming industries, and how you can apply these technologies in real-world scenarios.
Course Objectives
By the end of this course, participants will be able to:
- Understand the basic principles of AI and machine learning
- Differentiate between AI, ML, deep learning, and data science
- Explore real-world AI applications across industries
- Build and evaluate basic ML models using supervised and unsupervised learning
- Recognize ethical and business considerations in AI projects
Key Benefits of Attending
AI and ML are reshaping careers, organizations, and global economies. This course offers a strong foundation to understand, evaluate, and begin working with these technologies in a practical and ethical way—regardless of your industry or function.
Intended Audience
- Business leaders and decision-makers
- IT professionals and software developers
- Data analysts and operations teams
- Engineers and technical managers
- Anyone curious about AI and ML fundamentals
Individual Benefits
- Gain a competitive edge with future-proof skills
- Learn to apply ML concepts in your job function
- Explore career paths in AI and data science
Organization Benefits
- Drive innovation through AI-enabled strategies
- Improve operations with data-driven decision-making
- Upskill teams to support AI adoption and integration
Instructional Methdology
- Instructor-led sessions
- Live coding demos with Python
- Hands-on labs using tools like Jupyter Notebook & Scikit-learn
- Group discussions, case studies & quizzes
Course Outline
DETAILED 5-DAY COURSE OUTLINE (Customizable)
Training Hours: 07:30 AM – 03:30 PM
Daily Format: 3–4 Modules | Coffee breaks: 09:30 & 11:15 | Lunch Buffet: 01:00 – 02:00
Day 1: Foundations of Artificial Intelligence
- 07:30 – 09:30 – Module 1: What is AI? Definitions, History, and Types
- 09:45 – 11:15 – Module 2: Key Concepts: Data, Algorithms, and Models
- 11:30 – 01:00 – Module 3: Applications of AI in Business and Industry
Day 2: Introduction to Machine Learning
- 07:30 – 09:30 – Module 4: Supervised vs. Unsupervised Learning
- 09:45 – 11:15 – Module 5: ML Workflow: Data Collection to Deployment
- 11:30 – 01:00 – Module 6: Python Basics for ML – DataFrames & Libraries
Day 3: Building and Evaluating ML Models
- 07:30 – 09:30 – Module 7: Linear Regression & Classification Techniques
- 09:45 – 11:15 – Module 8: Model Training, Validation & Overfitting
- 11:30 – 01:00 – Module 9: Model Metrics – Accuracy, Precision, Recall
Day 4: Advanced Concepts and Tools
- 07:30 – 09:30 – Module 10: Decision Trees, k-Means, and Clustering
- 09:45 – 11:15 – Module 11: Intro to Neural Networks & Deep Learning
- 11:30 – 01:00 – Module 12: Hands-on Practice: Real Datasets in Jupyter
Day 5: Ethics, Strategy & Capstone
- 07:30 – 09:30 – Module 13: Bias, Fairness, and Ethics in AI
- 09:45 – 11:15 – Module 14: AI Strategy and Business Readiness
- 11:30 – 01:00 – Module 15: Final Project Presentation & Certification Ceremony
Certification
Participants will receive a Certificate of Completion in Fundamentals of Artificial Intelligence & Machine Learning, validating their knowledge of key AI/ML concepts and tools.