B.Tech Computer Science & Engineering with AI/ML

GNIOT Group of institutions
College
4 years Years
Duration
₹180000.00/year
Fees
Overview
Curriculum
Admission
Career Prospects

Course Overview

The course is designed to provide students with sufficient exposure to the variety of applications that can be built using techniques covered in this program. They will be able to apply AI/ML methods, techniques, and tools to these applications. Students will explore the practical components of developing AI apps and platforms. Proficiency in mathematics will be beneficial, as this degree requires strong problem-solving and analytical skills. They will acquire the ability to design intelligent solutions for various business problems across a range of domains and business applications. Students will delve into fields such as neural networks, natural language processing, robotics, deep learning, computer vision, reasoning, and problem-solving. The key objective is to identify logic and reasoning methods from a computational perspective, learn about agents, search methods, probabilistic models, perception, cognition, and machine learning. Students will be industry-ready after practicing AI/ML-based algorithms, techniques, and tools and applying them to various industries. This degree will provide expertise in problem-solving and analytical skills, along with the ability to design intelligent solutions for diverse business challenges.


 

Students graduating with a B.Tech. in Computer Science and Engineering specializing in Artificial Intelligence and Machine Learning (CSE-AIML) have a promising future with various career opportunities. Some potential career paths include:

  • AI/ML Engineer: Developing and implementing machine learning algorithms and AI systems for various applications such as healthcare, finance, e-commerce, and more.
  • Data Scientist: Analyzing large datasets, deriving insights, and building predictive models to solve complex business problems.
  • Software Developer: Creating software applications and systems that incorporate AI and machine learning capabilities.
  • Research Scientist: Conducting research in AI and ML, pushing the boundaries of technology, and contributing to advancements in the field.
  • AI Consultant: Providing expertise and guidance to organizations on how to leverage AI and ML technologies to improve their operations and products.
  • Robotics Engineer: Designing and developing robots and autonomous systems that utilize AI and ML algorithms for perception, decision-making, and control.
  • Natural Language Processing (NLP) Engineer: Working on projects related to language translation, sentiment analysis, chatbots, and voice recognition systems.
  • Machine Learning Operations (MLOps) Engineer: Managing the deployment, monitoring, and optimization of machine learning models in production environments.
  • AI Ethics Specialist: Addressing ethical considerations and biases in AI algorithms, ensuring fairness, transparency, and accountability in AI systems.
  • Entrepreneur: Starting their own AI-driven startups to solve specific problems or create innovative products and services.
Degree Awarded
Engineering
Course Level
undergraduate
Course Type
Engineering
Eligibility
10+2 with 50% in PCM
Entrance Exam
NA
Seats Available
0
Average Package
₹650000.00
Highest Package
₹7000000.00

Curriculum Structure

The course is designed to provide students with sufficient exposure to the variety of applications that can be built using techniques covered in this program. They will be able to apply AI/ML methods, techniques, and tools to these applications. Students will explore the practical components of developing AI apps and platforms. Proficiency in mathematics will be beneficial, as this degree requires strong problem-solving and analytical skills. They will acquire the ability to design intelligent solutions for various business problems across a range of domains and business applications. Students will delve into fields such as neural networks, natural language processing, robotics, deep learning, computer vision, reasoning, and problem-solving. The key objective is to identify logic and reasoning methods from a computational perspective, learn about agents, search methods, probabilistic models, perception, cognition, and machine learning. Students will be industry-ready after practicing AI/ML-based algorithms, techniques, and tools and applying them to various industries. This degree will provide expertise in problem-solving and analytical skills, along with the ability to design intelligent solutions for diverse business challenges.


 

Students graduating with a B.Tech. in Computer Science and Engineering specializing in Artificial Intelligence and Machine Learning (CSE-AIML) have a promising future with various career opportunities. Some potential career paths include:

  • AI/ML Engineer: Developing and implementing machine learning algorithms and AI systems for various applications such as healthcare, finance, e-commerce, and more.
  • Data Scientist: Analyzing large datasets, deriving insights, and building predictive models to solve complex business problems.
  • Software Developer: Creating software applications and systems that incorporate AI and machine learning capabilities.
  • Research Scientist: Conducting research in AI and ML, pushing the boundaries of technology, and contributing to advancements in the field.
  • AI Consultant: Providing expertise and guidance to organizations on how to leverage AI and ML technologies to improve their operations and products.
  • Robotics Engineer: Designing and developing robots and autonomous systems that utilize AI and ML algorithms for perception, decision-making, and control.
  • Natural Language Processing (NLP) Engineer: Working on projects related to language translation, sentiment analysis, chatbots, and voice recognition systems.
  • Machine Learning Operations (MLOps) Engineer: Managing the deployment, monitoring, and optimization of machine learning models in production environments.
  • AI Ethics Specialist: Addressing ethical considerations and biases in AI algorithms, ensuring fairness, transparency, and accountability in AI systems.
  • Entrepreneur: Starting their own AI-driven startups to solve specific problems or create innovative products and services.

Admission Process

The admission to B.Tech Computer Science program is based on entrance exam scores followed by counseling. Here's the step-by-step process:

1
Check Eligibility

Candidate must have passed 10+2 examination with Physics, Chemistry, and Mathematics as compulsory subjects with minimum 60% marks.

2
Appear for Entrance Exam

Appear for BCECE (Bihar Combined Entrance Competitive Examination) or JEE Main. The college accepts scores from both examinations.

3
Online Application

Fill the online application form on the college website during the application window (typically May-June).

4
Counseling Process

Shortlisted candidates will be called for counseling based on their entrance exam rank. Document verification and seat allotment happens during counseling.

5
Fee Payment & Enrollment

Selected candidates need to pay the admission fee and complete the enrollment process to confirm their seat.

Career Opportunities

Machine Learning Engineer

Build & deploy ML models

Skills: Python, TensorFlow, Scikit-Learn

 AI Engineer

Develop AI systems (chatbots, vision, automation)

Skills: Deep Learning, NLP, Computer Vision
 Data Scientist

Analyze big data & build predictive models

Skills: Python, SQL, Statistics

 Data Analyst

Data cleaning, visualization & reporting

Tools: Power BI, Tableau, Excel
 Software Engineer / Developer

Full-stack, backend or system development

Languages: Java, Python, C++
 NLP Engineer 

Work on speech & language models

Applications: Chatbots, voice assistants

 Computer Vision Engineer 

Image & video analysis

Used in self-driving cars, surveillance

 Robotics & Automation Engineer

AI-powered robots & automation

 Research Scientist (AI/ML)

R&D roles in labs & universities

Usually needs MTech / MS / PhD

Top Recruiters

  • TCS
  • Infosys
  • Wipro
  • Accenture
  • Amazon
  • Microsoft
  • Google
  • IBM

Apply for This Course

Application Deadline
February 04, 2026
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