Innovate your way to the future
This Artificial Intelligence Certification is designed to help you gain proficiency and prepare you for a promising career in artificial intelligence and machine learning.
This program covers machine learning, natural language processing, reinforcement learning, and other cutting-edge AI approaches in-depth and entirely online. After completing the program, you’ll be equipped with the knowledge and self-assurance needed to debug your code, create your own models free from the limitations of pre-made tools, and develop original models, tools, and algorithms.
From entry-level to expert job profiles are available with artificial intelligence. If you aim for high-end technical professions, you can become an AI, ML, or data scientist. Alternatively, you may pursue a career as a business analyst, robotics engineer, or computer vision engineer, depending on your interests.
Dr. Shehryar Najam
Qualification: Ph.D. Electrical Engineering
Teaching Experience: 10 Years
After the completion of this certification, students would be able to:
From entry-level to expert job profiles are available with artificial intelligence. If you aim for high-end technical professions, you can become an AI, ML, or data scientist. Alternatively, you may pursue a career as a business analyst, robotics engineer, or computer vision engineer, depending on your interests.
Sr No. | Contents |
---|---|
1 | Introduction to AI, History and Types |
2 | Intelligent Agent |
3 | Problem Solving in AI, AI Algorithms |
4 | Adversarial Search |
5 | Knowledge Representation, Knowledge-Based Agent |
6 | Propositional Logic |
7 | Rules of Inference |
8 | The Wumpus World |
9 | Unification in FOL, Resolution in FOL |
10 | Reasoning in AI |
11 | Uncertain Knowledge Representation |
12 | Bayes Theorem in AI |
13 | Bayesian Belief Network |
14 | Examples of AI |
15 | AI in Education, Engineering, and Healthcare |
16 | Engineering Applications in AI |
17 | Robotics in AI |
18 | AI Future, Approaches of AI Learning |
19 | Subsets of AI |
20 | Expert Systems, Machine Learning Basics |
21 | NLB Basics |
22 | Final Project |
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