Artificial Intelligence Course Syllabus – Introduction, MTech, and More

Artificial Intelligence Course Syllabus

The artificial intelligence course syllabus simulates human intelligence processes by machines, especially computer systems.

The Specific applications of AI include expert systems, natural language processing, speech recognition, and computer vision.

How does AI work?

As AI hype has accelerated, vendors have gone out of their way to promote how their crops and services use AI.

Often, AI is simply a component of AI, such as machine learning. The AI requires a foundation of specialized hardware and software to write and train machine learning algorithms.

No programming language is synonymous with AI, but some, including Python, R, and Java, are popular.

AI systems generally work by taking large amounts of labeled training data, analyzing the data for correlations and patterns, and utilizing these patterns to make predictions about future states.

This way, a chatbot that receives examples of text chats can learn to produce real connections with people, or an image recognition tool can learn to identify and describe objects in images by reviewing millions of examples.

The AI programming focuses on three cognitive abilities: learning, reasoning, and self-correction.

They are learning processes. This aspect of AI programming focuses on data acquisition and creating rules to turn data into actionable insights. The algorithms provide computing devices with step-by-step instructions on how to complete a specific task.

Cerebral processes. And also, this aspect of AI programming focuses on choosing the correct algorithm to achieve the desired result.

The Self-correction processes. This aspect of AI programming is designed to continuously fine-tune the algorithms to ensure they provide the most accurate results possible.

Artificial Intelligence Syllabus 2022

Here is the diverse Artificial Intelligence Course Syllabus taught commonly at all the course levels of study: Diploma, Undergraduate and Postgraduate.

Introduction to Artificial Intelligence – Introduction to Machine Learning

Introduction to Deep Learning Web Technologies

Database Management – Systems Programming

Discrete Structures – Computer Networks

Interface Technologies – Signal Processing

Introduction to Data Science – Computation Theories

Cryptography Internet of Things – (IoT)

Diploma in Artificial – Intelligence Syllabus

The detailed Diploma in Artificial Intelligence Syllabus is provided in the tabulation below:

Python Machine Learning and AI Frameworks – SQL

Machine Learning Foundations of AI and Machine Learning

Linear Algebra – Probability

Statistics – Essentials of Artificial Intelligence

Advanced Machine Learning with Deep Learning Plotting for Data Analysis:

Visualizing High-dimensional – Data Dimensionality Reduction

Deep Learning – Data Visualization and Analysis

Thesis Advanced Optimization Methods

BTech Artificial Intelligence Syllabus

Below is the tabular representation of the BTech Artificial Intelligence Syllabus, taught almost commonly in all the top institutions.

CAD and Drafting – Programming and Problem-solving

Introduction to AI – Advanced Physics

Engineering Chemistry – Mechanical Workshop

Discrete Structures – Computer Networks

The Design and Analysis of Algorithms – Software Engineering and Testing Methodologies

Principles of Operating System – Introduction to Biology for Engineering

Introduction to Deep Learning – Robotics and Intelligent Systems

OOPS, using JAVA – Management Studies

Web Technologies – Compiler Design

Theory of Computation – Neural Networks

MTech Artificial Intelligence Syllabus

A tabular representation of MTech Artificial Intelligence is provided in the table below:

AI and Artificial Neural Networks – Embedded Systems

AI-Based Programming Tools – Soft Computing

Knowledge Engineering and Expert Systems – Machine Learning

Human-Computer Interaction – Natural Language Processing

Image Processing and Machine Vision – Automated Reasoning

Signal Processing – Interface Technologies

Speech or Biometric Processing – Computational Intelligence

Agent-Based Intelligence Systems – Modeling and Simulation of Digital Systems

Problem-solving Methods – Cognitive Systems

Summer Internships – Projects

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