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The Nirwan University the School of Engineering & Technology offers B Tech Artificial Intelligence and Machine Learning program in collaboration with SAS, is primarily a 4-year undergraduate degree program, provided in the Engineering stream.

The student under B.Tech Artificial Intelligence and Machine Learning is required to write the code of the said machine. This code in essence works as guiding instruction for the machine, they said the machine is performing tasks with less human intervention. The 4-year full-time program presents exposure to hands-on technologies to create applications and solutions for the world that we live in. In this Course, Students are exposed to real-life applications of Artificial Intelligence and Machine Learning (AIML) from the third semester, with a strong emphasis on probability and applied statistics. This allows students to think about AIML applications in both practical and theoretical ways, enabling them to optimize models and solutions.

Eligibility

Passed 10+2 examination from BSER or equivalent with PCM

Lateral Entry Passed min. 3 years Diploma examination from UGC approved University with at least 45% marks

  • Duration
    4 Years
  • Fee/Sem
    50,000/-
    Examinations Fee (Per Semester)
    1,500/-
    Registration Fee
    500/-
    Enrollment Fee
    1,000/-

Highlights

  • This graduate program has a comprehensive coverage of applied and statistical methods used in Machine Learning and Artificial Intelligence while preparing the students to analyze, design and experiment solutions to problems.
  • The curriculum targets technical and design skills, AI knowledge, and competencies needed to master strategic in machine learning applications, and data management, with the objective of creating innovative strategies to solve challenging real-world problems.
Program-objective

Curriculum Details

  • Engineering Mathematics - I
  • Engineering Physics
  • Communication Skills
  • Programming For Problem Solving
  • Basic Electrical Engineering
  • Engineering Physics Lab
  • Language Lab
  • Computer Programming Lab
  • Basic Electrical Engineering Lab
  • Basic Electrical Engineering Lab

  • Engineering Mathematics - II
  • Engineering ChemistryM
  • Human ValuesM
  • Basic Mechanical EngineeringM
  • Basic Civil EngineeringM
  • Engineering Chemistry LabM
  • Human Values Activities And SportsM
  • Manufacturing Practices WorkshopM
  • Basic Civil Engineering LabM
  • Computer Aided Machine Drawing

  • Analytics Programming Fundamentals
  • Sas Programming In Viya
  • Engineering Mathematics - Iii
  • Digital Electronics
  • Data Structures And Algorithms
  • Object Oriented Programming
  • Digital Electronics Lab
  • Data Structures And Algorithms Lab
  • Object Oriented Programming Lab

  • Sas Enterprise Guide: Anova, Regression And Logistic Regression
  • Application Of Machine Learning Using Sas(r) Viya
  • Microprocessor
  • Database Management System
  • Theory Of Computation
  • Data Communication And Computer Networks
  • Microprocessor Lab
  • Database Management System Lab
  • Network Programming Lab
  • Linux Shell Programming Lab
  • Java Lab

  • Sas Visual Text Analytics In Sas Viya
  • Neural Network: Essentials
  • Compiler Design
  • Operating System
  • Computer Graphics And Multimedia
  • Analysis Of Algorithms
  • Open Elective – I (any One)
  • Wireless Communication
  • Computer Graphics And Multimedia Lab
  • Compiler Design Lab
  • Analysis Of Algorithms Lab
  • Advance Java Lab

  • Deep Learning Using Sas Software
  • Digital Image Processing
  • Machine Learning
  • Computer Architecture And Organization
  • Artificial Intelligence
  • Cloud Computing
  • Department Elective – I (any One)
  • Distributed System
  • Software Defined Network
  • Ecommerce And Erp
  • Digital Image Processing Lab
  • Machine Learning Lab
  • Python Lab
  • Mobile Application Development Lab

  • Forecasting Using Model Studio In Sas Viya
  • Optimization Concepts For Data Science And Artificial Intelligence
  • Internet Of Things
  • Internet Of Things Lab
  • Big Data Analytics
  • Big Data Analytics Lab
  • Software Testing And Validation Lab
  • Open Elective–ii (any One)
  • Wind And Solar Energy Systems
  • Quality Management
  • Automobile Engineering
  • Water Resource Engineering
  • Open Elective–iii (any One)
  • Energy Auditing
  • Engineering Thermodynamics
  • Principles Of Management
  • Air & Noise Pollution And Control

  • Internship (18 Weeks Minimum)
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Program Outcomes (POs)

  • PO1

    Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an Engineering specialization to the solution of complex engineering problems.

  • PO2

    Problem analysis: Identify, formulate, research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and Engineering sciences.

  • PO3

    Design/development of solutions: Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations.

  • PO4

    Conduct investigations of complex problems: Use research–based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.

  • PO5

    Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern Engineering and IT tools including prediction and modelling to complex Engineering activities with an understanding of the limitations.

  • PO6

    The engineer and society: Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional Engineering practice.

  • PO7

    Environment and sustainability: Understand the impact of the professional Engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.

  • PO8

    Apply ethical principles and commit to professional ethics and responsibilities and norms of the Engineering practice.

  • PO9

    Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.

  • PO10

    Communication: Communicate effectively on complex Engineering activities with the Engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.

  • PO11

    Project management and finance: Demonstrate knowledge and understanding of the Engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.

  • PO12

    Life – long learning: Recognize the need for, and have the preparation and ability to engage in independent and life – long learning in the broadest context of technological change.

Programme Specific Outcomes

  • PSO1

    Able to apply the knowledge gained during the course of the program from Mathematics, Basic Computing, and Basic Sciences in general and all Computer Science and Engineering courses in particular to identify, formulate and solve real life problems faced in industries and/or during research work.

  • PSO2

    Able to provide socially acceptable technical solutions to complex Computer Science and Engineering problems with the application of modern and appropriate techniques for sustainable development.

  • PSO3

    Able to apply the knowledge of ethical and management principles required to work in a team as well as to lead an industry.

Program Educational Objectives (PEO)

Students should be in position to solve the real time problems related to Computer Science and engineering, and its relevant equipment depending upon the present – day demand based on effectiveness innovation.

Students should be capable enough to formulate the design problem based on the customize demand of the country and citizen.

Students should be in position to demonstrate the skill set developed related to field of Computer Science and Engineering.

After learning the basic skills through the B. Tech. Computer Science and Engineering courses, student should have spark and intention to learn and explore more on its favorite field of interest.

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outcomes

Career Path

  • Data Scientist
  • Machine Learning Engineer
  • Research Scientist
  • Business Intelligence Developer
  • AI Data Analyst
  • Big data engineering
  • Robotics Scientist
  • AI engineer

FAQ

Who is this Machine Learning course ideal for?

Professionals eager to develop AI and ML expertise with the objective of: 

  • Enhancing effectiveness in their current role
  • Transitioning to AI roles in their organization
  • Seeking to advance their career in the industry
  • Giving shape to entrepreneurial aspirations
What are some of the job profiles after B. Tech in AI & ML?

Some of the job profiles which are highly suitable after completion of this course are Data Analyst, Data Scientist, Data Engineer, Principle Data Scientist and Computer Vision Engineer.

What is the minimum income level on getting a job after completing B. Tech. in Artificial Intelligence and Machine?

A student graduating from a reputed college in B.Tech in Artificial Intelligence and Machine is expected to earn a minimum of 10 lakh per annum.

Campus
Nirwan University Jaipur

Near Bassi-Rajadhok Toll, Agra Road, Jaipur- 303305

City Office

21, Sahkar Marg, 1st Floor, Near 22 Godam Circle
Jaipur - 302019 Rajasthan
Campus

Nirwan University

Near Bassi-Rajadhok Toll, Village- Jhar, Agra Road, Jaipur - 303305 Rajasthan
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