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Course Description

The "Certificate Course in Artificial Intelligence" offered by LBS (LBS Centre For Science & Technology) is a specialized certification program designed to provide individuals with comprehensive knowledge and practical skills in the field of artificial intelligence (AI). As AI continues to transform various industries, this program ensures that participants are well-prepared to harness the power of AI in their careers. The curriculum covers a wide range of AI topics, including machine learning, deep learning, natural language processing, computer vision, and AI applications across industries. Participants gain hands-on experience with AI tools, technologies, and programming languages. The program is designed to equip individuals with the ability to develop AI models, analyze data, and apply AI solutions to real-world problems. Upon successful completion of the "Certificate Course in Artificial Intelligence" by LBS, participants are well-prepared for careers in AI research, data science, AI development, and related fields, where AI expertise is highly sought after. Join us on this educational journey to become a proficient AI professional, contributing to advancements in technology and problem-solving using artificial intelligence.
  • Affiliation

    LBS

  • Topics

    Introduction What Is AI? The Foundations of Artificial Intelligence, The History of Artificial Intelligence, (Russel), Overview of AI Application Areas, Artificial lntelligence - A Summary (Text book 3) Problem solving basics Problems, Problem Spaces, and Search. Defining the Problem as a State Space Search. Problem Characteristics, Production Systems, Production System Characteristics. Issues in the Design of Search Programs (Text book 1) Solving Problems by Searching Uninformed Search: Formulating the State Space, Components of Implicit State-Space Graphs, Breadth-First Search, Depth-First or Backtracking Search, Iterative Deepening (Text book 5) Heuristic Search Techniques: Generate-and-Test, Hill Climbing, Best-first Search (Text book 1) Algorithm A*, Admissibility of A*, Iterative Deepening A*, Recursive Best First Search (Text book 4) AO* algorithm, Constraint Satisfaction. Crypt Arithmetic Problems (Text book 1) Advanced Searchtechniques Heuristics in Games, Design of good heuristic-an example. Min-Max Search Procedure, Alpha Beta pruning, (Text book 3) Knowledge representation Using Predicate logic - representing facts in logic, functions and predicates, Conversion to clause form, Resolution in propositional logic, Resolution in predicate logic, Unification. Representing Knowledge Using Rules: Procedural Versus Declarative knowledge, Logic Programming, Forward versus Backward Reasoning. (Text book 1) Structured Knowledge representation The Schema, Frames, The Semantic Net Scripts, Goals, Plans and MOPs , Conceptual Graphs. (Text book 4) Advanced Problem Solving Introduction to agent based problem solving. Strong Method Problem Solving - an introduction. Overview of Expert System Technology. Rule-Based Expert Systems (Text book 3) Expert System Shells –Support for explanation- examples –Knowledge acquisition-examples. (Text book 1) Reasoning in Uncertain situations Introduction to Logic-Based Abductive Inference. Abduction: Alternatives to Logic. The Stochastic Approach to Uncertainty. (Text book 3) Learning What is learning, Rote learning. Learning by taking Advice. Learning in Problem-solving, Learning from example: induction, Explanation-based learning. (Text book 1) Introduction to Reinforcement Learning, Passive Reinforcement Learning, Active Reinforcement Learning. Applications of Reinforcement Learning (Text book 2) Machine Learning Naive Bayes Classifiers, Decision Trees, The k-means Clustering Algorithm Artificial Neural Networks (Text book 4) Planning Forward State Space Planning, Backwards State Space Planning, Goal Stack Planning, Plan Space Planning, A Unified Framework for Planning (Text book 4) Natural Language Processing Classic Problems in NLP and Schools of Thought, Basic NLP Techniques, Applications (Text book 4) Programming Techniques for Artificial Intelligence An Introduction to Prolog, Syntax for Predicate Calculus Programming. Abstract Data Types (ADTs) in PROLOG. A Production System Example in PROLOG (Text book 3) An Introduction to LISP and a brief overview. Search in LISP: A Functional Approach to the Farmer, Wolf, Goat, and Cabbage Problem (Text book 3) Conclusions AI: Current Challenges and Future Directions (Text book 3) Are we going in the right direction? What If AI does succeed? The Ethics and Risks of Developing Artificial Intelligence (Text book 2)

  • Duration

    3 Months

Our Branches Offering Certificate Course in Artificial Intelligence

Our Branches Offering Certificate Course in Artificial Intelligence

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