Find the Best Engineering College in Noida with Latest AI and ML Syllabus

There is a growing demand for skilled and experienced professionals in Artificial Intelligence (AI) and Machine Learning (ML) across various sectors such as health care, automation, cyber security, finance and more. This is also the case with India, where AI professionals are constantly in demand as the country is moving towards an AI-powered economy.

This makes pursuing B Tech Artificial Intelligence and Machine Learning a strategic career investment instead of just a niche choice. If you have just completed your 12th and want to pursue a specialised B Tech program, then choosing B Tech Artificial Intelligence and Data Science can be a riveting choice.

 

However, before you go through with the admission process, it is first necessary to get an adequate comprehension of the syllabus and subject structure for the course. The purpose of the article is to help you understand the syllabus Structure of B Tech in AI and machine learning by breaking it down by subject, semester and career prospects.

This will help you make better and informed decisions regarding admission by exploring the best engineering colleges in Noida and other parts of the country.

 

Need for understanding the AI and ML syllabus

Artificial Intelligence and machine learning field are evolving rapidly. The technologies that were considered cutting-edge yesterday have become a thing of past, and that is why most institutions and Universities across engineering colleges in Noida have upgraded their B Tech Artificial Intelligence and data science course syllabus for 2025.

 

Some of the key trending topics, which have been integrated in the courses, include:

• AI model deployment through MLOps
• Edge AI
• Generative AI such as ChatGPT and DALL-E
• AI in cybersecurity
• Responsible and ethical AI

 

Understanding of the semester-wise syllabus of B Tech in AI and machine learning

The B Tech Artificial Intelligence and Data Science program in India is a four-year undergraduate course, which is divided into 8 different semesters. Below is provided the latest curriculum structure of these semesters according to the top engineering colleges in the country.

 

Semester 1 and 2: Programming and Engineering Foundation

The first year provides the basic foundation to develop programming skills and engineering principles necessary for the development of AI and ML.

 

Subjects 

• Engineering Mathematics I & II
• Physics for Engineers
• Basics of Electrical and Electronics
• Data structures
• Programming in C / C++
• Engineering Drawing
• Communication Skills

 

Lab work includes Physics and Chemistry projects and programming. You will gain mathematical and logical thinking and acquire proficiency in basic coding in year 1.

 

Semester 3: Introduction to Artificial Intelligence and Algorithms

This is where students begin to delve deeper into core computing and integrate AI concepts.

 

Subjects

• Data Structures & Algorithms
• Design and analysis of algorithms
• Object-Oriented Programming using Java or Python
• Introduction to Artificial Intelligence
• Web technologies such as HTML, JavaScript and CSS
• Probability and Statistics
• Operating Systems and networking

 

Lab work includes database projects, algorithm design and network simulation. Students will acquire data handling techniques and comprehend the basics of AI, such as search algorithms, knowledge representations, and agents.

 

Semester 4: Natural Language Processing (NLP) foundations and core machine learning

In the semester, students learn to build deep learning and NLP models.

 

Subjects

• Machine Learning Fundamentals
• Discrete Mathematics
• Natural Language Processing
• Database Management Systems
• Computer Organization & Architecture

 

The key lab works include machine learning using the Python lab and the NLP toolkit lab.  You will learn to train ML models and use them to extract and process data.

 

Semester 5: Neural networks and deep learning

The main focus of the semester is to build a critical understanding of deep learning concepts, CNNs, RNNs and apply artificial intelligence in the real world.

 

Subjects

• Deep Learning
• Pattern Recognition
• AI Ethics and Law
• Web Technologies (for AI-based web apps)
• Software Engineering Principles

 

Lab works include building, training and using neural networks through TensorFlow, Keras, and learning deployment of AI practices in real time.

 

Semester 6: Cloud AI, Applied AI and Big Data

The semester focuses on scaling the use of AI by understanding data platforms and the cloud.

 

Subjects

• Big Data Analytics using Hadoop/Spark
• Cloud Computing for AI (AWS/GCP/Azure)
• Computer Vision and Image Processing
• Human-Computer Interaction
• AI in Robotics

 

The key lab work includes big data lab, CV lab using OpenCV, and cloud-based AI deployment. This will help you gain hands-on experience of using cloud platforms and applying AI for robotics and vision tasks.

 

Semester 7: MLOps, electives and Research projects

This is where students will begin to work on real projects and select electives according to their preferences and interests.

 

Subjects

• MLOps & Model Deployment
• Research Methodology
• Project Work (AI-based application or product)

 

Popular electives

• Reinforcement Learning
• Blockchain for AI
• AI in Cybersecurity
• AI in Healthcare
• Edge Computing

 

The semester will help you master full-cycle ML deployment through CI/CD pipelines and monitoring and solving real-world complex problems using AI.

 

Semester 8: Internship, capstone project and industry integration

The last semester will mainly focus on projects and integration into the relevant industry.

 

Activities

• Industry-relevant internship (6 months)
• Research project
• Capstone project

 

After completing the semester, you will be able to build a worthy project-based portfolio, gain industry experience and transition to higher studies or job.

 

Core subjects in B Tech Artificial Intelligence and machine learning curriculum

Regardless of the institution or B Tech in AI and machine learning you have opted for, there are certain subjects that will be common and act as a backbone for your career in AI. These include:

 

Core AI and ml subjects

• Artificial Intelligence Fundamentals
• Machine Learning (Supervised, Unsupervised)
• Deep Learning
• Natural Language Processing
• Computer Vision
• Reinforcement Learning
• Generative AI Models

 

Programming

• Python, R, Java, C++
• TensorFlow, PyTorch
• Jupyter Notebooks
• Git, Docker, Kubernetes (for MLOps)
• Scikit-learn, Keras, OpenCV

 

Mathematics

• Linear Algebra
• Probability & Statistics
• Calculus
• Optimization Techniques

 

Applied AI domains

• AI in Healthcare
• AI in Finance
• AI for Social Good
• AI-powered Cybersecurity

 

Top colleges offering B Tech in AI and ML

Delhi NCR, specifically Noida, is considered a tech hub with many multinational organisations based in the region. This is why there are numerous engineering colleges in Noida that offer B Tech in AI and machine learning, which you can choose from. Below is a list of the top B Tech colleges in Noida that can help you begin your career in the field.

• Gautam Buddha University, Greater Noida
• United College of Engineering and Research, United Group of Institutions, Greater Noida
• KCC Institute of Technology and Management, Greater Noida
• Shiv Nadar University, Greater Noida

 

The total tuition fees for B Tech in AI and machine learning range from INR 3 Lakh to 10 Lakh.

 

Overall, it can be said that choosing a B Tech Artificial Intelligence and machine learning program after 12th can be the wisest decision a student can take to pursue a successful career in the IT field. There are numerous quality engineering colleges in Noida, from which you can choose to attend B Tech. However, it is extremely critical that you find an institution that has the latest AI and ML curriculum in 2025.