Artificial Intelligence(AI)

Learn Artificial Intelligence(AI) the exam way—clear concepts, worked examples, and 52 focused lessons in emerging technology.

Instructor: DAKALA SREENIVASULU

Last updated Aug 2026 en

64 learners enrolled

all-levels

This course includes

— on-demand video
Access on mobile & desktop
Full lifetime access
Certificate of completion

Course content

8 sections · 52 lectures

Lec-01: Artificial Intelligence Preview
Lec-02 : Artificial intelligence (AI)
Lec-03 : Intelligence composed of
Lec-04 : Agents in AI - 1
Lec-05 : Agents in AI - 2
Lec-06 : AI agents Types - 1
Lec-07 : AI agents Types - 2
Lec-08 : Agents environment

Lec-09 : Problem solving Preview
Lec-10 : Search algorithm | properties
Lec-11 : Search algorithm | Types
Lec-12 : BFS : Breath First Search algorithm
Lec-13 : BFS : Breath First Search algorithm Example
Lec-14 : DFS : Depth First Search algorithm
Lec-15 : DLS : Depth Limited search algorithm
Lec-16 : UCS : Uniform Cost Search algorithm
Lec-17 : Bidirectional search algorithm

Lec-18 : BFS algorithm Preview
Lec-19 : BFS algorithm example
Lec-20 : A Star algorithm
Lec-21 : A Star algorithm
Lec-22 : AO star algorithm

Lec-23 : knowledge based agent Preview
Lec-24 : Propositional logic
Lec-25 : wumpus world problem
Lec-26 : Wumpus world problem
Lec-27 : Wumpus world

Lec-28 : First Order Logic (FOL) Preview
Lec-29 : Atomic sentence
Lec-30 : Quantifiers in Ai
Lec-31 : FOL using quantifiers
Lec-32 : Inference in FOL
Lec-33 : Inference rules for quantifiers
Lec-34 : Unification | FOL
Lec-35 : unification algorithm and example
Lec-36 : Resolution in FOL
Lec-37 : Resolution example

Lec-38 : Forward chaining example Preview
Lec-39 : Forward chaining Example-2
Lec-40 : Backward chaining example
Lec-41 : Forward & Backward chaining | Differences

Lec-42 : AI techniques Preview
Lec-43 : Game playing
Lec-44 : Natural Language Process (NLP)
Lec-45 : Expert Systems
Lec-46 : Robotics

Lec-47 : Learning from observation Preview
Lec-48 : Inductive learning
Lec-49 : Decision tree learning Algorithm
Lec-50 : Decision tree Learning example
Lec-51 : AI Applications
Lec-52 : AI Applications

Explore related topics

Computer Science all-levels

Description

Artificial Intelligence(AI) is an exam-focused emerging technology programme designed for B.Tech / MCA learners and anyone revising CS subjects for semester exams (all levels). Lessons are paced for semester revision and competitive practice, with clear explanations you can replay anytime.

You will connect definitions to exam-style problems in Artificial Intelligence(AI), so you can write clearer answers, dry-run code mentally, and revise units in order. Syllabus highlights include Introduction & Agents, Uninformed Search Algorithms, Informed Search Algorithms, Propositional logic, First Order Logic (FOL), and Forward & Backward Chaining. Across 52 lessons, you will move from foundations to problem-solving patterns that show up in university papers and placement tests.

Taught by DAKALA SREENIVASULU, this course keeps theory short and practice heavy—so you can revise faster, spot examiner cues, and build confidence before mocks and finals.