NCC Short Course in Artificial Intelligence

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Course Overview

The NCC Education Short Course in Artificial Intelligence (AI) is designed to provide a comprehensive introduction to AI, exploring both theoretical and practical aspects. The course is tailored to meet the needs of different learning cohorts, including working professionals and entry-level graduates. It aims to equip learners with essential AI knowledge and skills to apply in various business and technical contexts.

Topics Covered

  • Introduction to AI
  • Problem Solving Using
  • Search
  • Knowledge
  • Representation
  • Uncertain Knowledge
  • Fuzzy Logic
  • Machine Learning
  • Neural Networks
  • Decision Trees
  • Genetic Algorithms
  • Expert Systems
  • Natural Language
  • Processing
  • Intelligent Agents

Entry Requirements

Academic Requirements
There are no formal prerequisites for this course. It is suitable for individuals looking to understand the basics of AI, regardless of their prior knowledge or experience.

Learning Outcomes

Upon completion, students will be able to:

  • Understand the importance and applications of AI.
  • Apply AI search strategies and knowledge representation techniques.
  • Assess techniques for reasoning with uncertain knowledge.
  • Understand machine learning techniques and their applications.
  • Implement and evaluate AI models and techniques in real-world problems.

Syllabus Content

Introduction to AI
Definitions, History of AI, Characteristics, Limitations, Ethics, and Development.

Problem Solving Using Search
Strategies for state space search, including uninformed and informed search.

Knowledge Representation
Types of knowledge, logical representation, semantic networks, frame representation, and production rules.

Uncertain Knowledge
Understanding uncertainty, probability, Bayes’ rule, and reasoning.

Fuzzy Logic
Fuzzy logic, linguistic variables, sets and operations, rules, and systems.

Machine Learning
Introduction to supervised, unsupervised, and reinforcement learning, and applications.

Neural Networks
Basic structure, perceptrons, multilayer networks, learning algorithms.

Decision Trees
Structure, terminologies, and attribute selection.

Genetic Algorithms
Basics of genetic algorithms and natural evolution simulation.

Expert Systems
Development, components, characteristics, and rule-based systems.

Natural Language Processing
Terminologies, components, processing pipeline, and applications.

Intelligent Agents
Concepts of agents, environments, rationality, and algorithms.

Assessment Strategy

Assessments are conducted through quizzes, assignments, and practical activities to evaluate students’ understanding and application of AI concepts. There are no formal examinations.

Career and Professional Development

This course prepares students for various AI career paths, including:

  • AI Architect
  • Business Intelligence Developer
  • Big Data Engineer
  • Data Scientist
  • Machine Learning Engineer

Support for Student Learning:

Students will have access to:

Learning Resources
Online study materials and libraries.

Discussion Forums
For engagement with peers and tutors.

Technical Support
Available throughout the course duration.

Programming Tools Used

  • WEKA
  • Scikit-Learn
  • Python (with NLTK)
  • SWI Prolog

Total Qualification Time:

Approximately 80 hours, including video lectures, practical activities, and assessments.

Conclusion

The NCC Short Course in Artificial Intelligence (AI) equips learners with a solid understanding of AI principles and practical applications, enabling them to explore opportunities in the evolving AI field. Whether advancing a career or pursuing further studies, this course provides the essential knowledge and skills to thrive in an AI-driven world.

Entry Requirements

Assessment Strategy