Programme Parameters
Foundation
4 Weeks (40 Hrs)
Online (e-LMS)
• No prior experience required — basic computer literacy is sufficient.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.
About This Course
The Introduction to Artificial Intelligence course is a free, beginner-friendly self-paced program designed to help learners understand the fundamentals of AI. The course explains what artificial intelligence is, how it works, and how it is used in real-world applications. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
The Introduction to Artificial Intelligence course is a free, beginner-friendly self-paced program designed to help learners understand the fundamentals of AI. The course explains what artificial intelligence is, how it works, and how it is used in real-world applications.
📋 Course Objectives
1. Put Artificial Intelligence techniques to work on real datasets and case studies.
2. Assemble a documented case study that evidences your applied capability.
👥 Who Should Enroll?
• Master's and senior undergraduate students specializing in Artificial Intelligence
• R&D engineers and working professionals applying Artificial Intelligence in industry
• Academics and educators building research or teaching capacity in Artificial Intelligence
🚀 Key Learning Outcomes
• A demonstrable Artificial Intelligence project for your research or industry portfolio.
• A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
💎 What You'll Gain
Live & Recorded Sessions
Lifetime access to class recordingse-Certificate on Completion
Cryptographically verified credentialPost-Programme Support
Direct access to mentors & councilHands-On Experience
Notebooks, real-world code & datasetsCurriculum Outline
Introduction to Artificial Intelligence
What is Artificial Intelligence? • History and Evolution of AI • AI vs Machine Learning vs Data Science • Applications of AI in Everyday Life
How AI Works
Basic Concepts of Data and Algorithms • Introduction to Machine Learning • Rule-Based Systems vs Learning Systems • Examples of AI Systems
Types of AI and Applications
Narrow AI vs General AI • AI in Healthcare, Business, Finance, and Technology • Automation and Intelligent Decision-Making • Future of AI and Emerging Trends
Responsible and Ethical AI
Understanding AI Ethics • Bias and Fairness in AI Systems • Privacy and Data Concerns • Responsible Use of AI
AI Learning Path and Career Basics
Careers in Artificial Intelligence • Skills Required for AI and Data Science • Learning Path for Beginners • Next Steps in AI, Machine Learning, and Data Science
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | Artificial Intelligence |
| Covered Tool / Platform | Machine Learning Basics |
| Covered Tool / Platform | Data Concepts |
| Covered Tool / Platform | Automation |
| Covered Tool / Platform | AI Applications |
Frequently Asked Questions
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