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COURSE OVERVIEW

The theory and development of computer systems that can perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation and interpretation are formalized as AI. Machine learning is a method of data analysis that automates analytical model building. The adoption of artificial intelligence/ Machine Learning (AI/ML) is growing worldwide. Organizations worldwide are adopting AI/ML in their business transformation journey for agility, resilience, innovations, and scalability. With this backdrop. The Apollo University offers a four-year under-graduate B. Tech CSE (Artificial Intelligence and Machine Learning) for laying a strong foundation by using the principles and technologies that consist of many facets of Artificial Intelligence including logic, knowledge representation, probabilistic models, and Machine Learning. This program is best suited for students seeking to build world- class expertise in Artificial Intelligence and Machine Learning and emerging technologies which help to stand apart in the crowd and grow careers in the upcoming technological era.

SYLLABUS >

Program Objectives

  • The students will able to acquire the ability to design intelligent solutions for various business problems in a variety of domains and business applications and also explore fields such as neural networks, natural language processing, robotics, deep learning, computer vision, reasoning, and problem-solving.
  • The students will get acquittance with machine learning methods, tools, and computer algorithms used to train machines to analyze, understand, and find hidden patterns in data and make predictions.
  • The eventual goal is to utilize data for self-learning, eliminating the need to program machines in an explicit manner.
  • Identify problems where artificial intelligence techniques are applicable.
  • Applying selected basic AI techniques; judge applicability of more advanced techniques.

Industry leader speak

The term Artificial Intelligence and Machine Learning have created a lot of buzz over the past several years with all the talk on autonomous vehicles, data analysis on a massive scale, and the world’s leading organizations relying on machine learning and deep learning algorithms to improve business intelligence and refine business strategy. It was also considered to be among the most advanced technologies and techniques used to deploy artificial neural networks. Those dealing in computer science and engineering industries will find it beneficial to implement Artificial Intelligence and Machine Learning as they will be in high demand with the evolution of these technologies.

Challa Vijay Kumar

Technical Manager

Galaxe Solutions India Pvt. Ltd.

PROGRAM HIGHLIGHTS

Students will have different career options after finishing graduation in AI & ML, such as

The programme has an unmatched range & depth, and covers the widest variety of skill & knowledge areas required to develop advanced AI solutions.
Aiming to become expert Machine Learning Engineers & AI Scientists.
The programme offers a set of core courses and elective courses, allowing students to gain expertise in Advanced Deep learning, Computational Learning theory, Speech Processing, Natural Language Processing, etc..

Programme Curriculum

  • Course Code Course Name Periods
    per week    		 Credits
    L T P
    BTMT1701 Engineering Physics 3 1 0 4
    BTMT1702 Engineering Mathematics 3 1 0 4
    BTMT1801 Problem Solving and Programming with C 3 1 0 4
    BTMT1101 Communicative English 3 0 0 3
    BTMT1201 University Elective I 3 0 0 3
    BTML1701 Engineering Physics Lab 0 0 3 1.5
    BTML1801 Problem Solving and Programming with C
    Lab    		 0 0 3 1.5
    TOTAL 15 3 6 21
  • Course Code Course Name Periods
    per week    		 Credits
    L T P
    BTMT1703 Probability & Statistics 3 1 0 4
    BTMT1802 Basic Electrical and Electronics Engineering 3 1 0 4
    BTMT1301 Data Structures 3 1 0 4
    BTMT1302 Python Programming 3 1 0 4
    BTMT1102 Environmental Studies 3 0 0 0
    BTMT1202 University Elective II 3 0 0 3
    BTML1802 Basic Electrical and Electronics Engineering
    Lab    		 0 0 2 1
    BTML1301 Data Structures Lab 0 0 2 1
    BTML1302 Python Programming Lab 0 0 2 1
    TOTAL 18 4 6 22
  • Course Code Course Name Periods
    per week    		 Credits
    L T P
    BTMT2701 Discrete Mathematics and Graph Theory 3 1 0 4
    BTMT2301 Design and Analysis of Algorithms 3 1 0 4
    BTMT2302 Object Oriented Programming through Java 3 0 0 3
    BTMT2801 Digital Logic design 3 0 0 3
    University Core – III 3 0 0 3
    University Elective -III 3 0 0 3
    BTMT2303 Constitution of India 3 0 0 0
    BTML2301 Java Programming Lab 0 0 2 1
    BTML2801 Digital Logic Design lab 0 0 2 1
    TOTAL 21 2 4 22
  • Course Code Course Name Periods
    per week    		 Credits
    L T P
    BTMT2702 Deterministic     Stochastic     and     Statistical
    Methods    		 3 1 0 4
    BTMT2901 Management for Engineers 3 0 0 3
    BTMT2501 Artificial Intelligence 3 0 0 3
    BTMT2304 Database Management Systems 3 0 0 3
    BTMT2305 Operating Systems 3 1 0 4
    BTMT2502 Machine Learning 3 0 0 3
    BTMT2306 Universal Human Values 3 0 0 0
    BTML2302 Database Management Systems Lab 0 0 2 1
    BTML2501 Machine Learning Lab 0 0 2 1
    — Internship – I will be Evaluated in V Sem – – – –
    TOTAL 21 2 4 22
  • Value Added Courses
    Course Code Course Name
    BTMA0001 Getting Started with Google Cloud Learning Path
    BTMA0002 Fundamentals of Data Analytics
    BTMA0003 Introduction to Blockchain Technology
    BTMA0004 Oracle Cloud Infrastructure Architect

     

    V – Semester
    Course Code Course Name Periods
    per week    		 Credits
    L T P
    BTMT3301 Computer Networks 3 0 0 3
    BTMT3302 Automata and Compiler Design 3 1 0 4
    BTMT3501 Data Analysis and Visualization 3 0 0 3
    BTMT3401 Faculty Elective – I 3 0 0 3
    BTMT3601 Programme Elective – I 3 0 0 3
    BTMM3501 MOOC – I 0 0 0 3
    BTML3501 Computer Networks Lab 0 0 2 1
    BTML3502 Data Visualization Lab 0 0 2 1
    BTMI3301 Internship-I Evaluation 0 0 4 2
    TOTAL 15 1 8 23

     

    Faculty Elective -I Program Elective -I
    Course Code Course Name Course
    Code    		 Course Name
    BTMT3401a Object Oriented Analysis and
    Design    		 BTMT3601a Software Engineering
    BTMT3401b Software Engineering BTMT3601b Applications of AI
    BTMT3401c Artificial Intelligence BTMT3601c Digital Marketing Analytics
    BTMT3401d Computer Organisation and
    Architecture    		 BTMT3601d Intelligent Multi Agent and Expert System
    BTMT3401e Software Engineering BTMT3601e Machine Learning
    Operations
    BTMT3401f Advanced Data Structures
    BTMT3401g Data Warehousing and Mining
    BTMT3401h Machine Learning
    BTMT3401i Differential Equations and Vector
    Calculus
    BTMT3401j Numerical Methods for Engineers
    BTMT3401k Mathematical Foundations of Cyber
    Security
    BTMT3401l Information Retrieval Systems
    BTMT3401m Cryptography and Network
    Security
    BTMT3401n Principles of Programming
    Languages
    BTMT3401o Unix and Shell Programming
    BTMT3401p Introduction to Psychology
    BTMT3401q Industry 4.0
    BTMT3401r Computer Vision
  • Value Added Courses
    Course Code Course Name
    BTMA0005 Database Engineer Learning Path
    BTMA0006 Big Data Foundation Course
    BTMA0007 Programming Basics for Blockchain Engineers
    BTMA0008 Oracle Cloud Security Administrator

     

    VI – Semester
    Course Code Course Name Periods
    per week    		 Credits
    L T P
    BTMT3502 Natural Language Processing 3 0 0 3
    BTMT3503 Advanced Machine Learning 3 0 0 3
    BTMT3402 Faculty Elective – III 3 0 0 3
    BTMT3602 Programme Elective – II 3 0 0 3
    BTMT3603 Programme Elective – III 3 0 0 3
    BTMM3502 MOOC – II 0 0 0 3
    BTML3503 Natural Language Processing Lab 0 0 2 1
    BTML3504 Advanced Machine Learning Lab 0 0 2 1
    — Internship – II will be Evaluated in VII Sem
    TOTAL 15 0 4 20

     

    Faculty Elective -II Program Elective -II
    Course Code Course Name Course Code Course Name
    BTMT3402a Design Patterns BTMT3602a Machine Intelligence for Medical
    Images
    BTMT3402b Cyber Security BTMT3602b Evolutionary Computation and
    Opinion Mining
    BTMT3402c Software Project
    management    		 BTMT3602c Practical Machine Learning with
    TensorFlow
    BTMT3402d Linux Programming BTMT3602d Cryptography and Network Security
    BTMT3402e Cloud Computing BTMT3602e AI for Robotics
    BTMT3402f Mobile Computing Program Elective -III
    BTMT3402g Image Processing BTMT3603a Software Testing Methodologies
    BTMT3402h Deep Learning BTMT3603b AI& ML in Health Care
    BTMT3402i E-Commerce BTMT3603c Human Machine Interaction
    BTMT3402j Block Chain Technology BTMT3603d Predictive Analytics
    BTMT3402k Mathematical Foundations of
    Data Science    		 BTMT3603e Nature Inspired Algorithms
    BTMT3402l Transforms and Boundary
    Value Problems
    BTMT3402m Optimization Techniques
    BTMT3402n Information Security
    BTMT3402o Ethical Hacking
    BTMT3402p Internet of Things
    BTMT3402q Embedded Systems
    BTMT3402r Green Computing
    BTMT3402s Cloud Security
    BTMT3402t DevNet
    BTMT3402u Advanced Computer
    Networks
    BTMT3402v Network Security
    BTMT3402w Fault Tolerant Systems
    BTMT3402x Computational Intelligence
    BTMT3402y Data Analytics with Tableau
  • Value Added Courses
    Course Code Course Name
    BTMA0009 Machine Learning Engineer Learning Path
    BTMA0010 BDA Foundation
    BTMA0011 Blockchain Essentials
    BTMA0012 Oracle Cloud Operations Engineer

     

    VII – Semester
    Course Code Course Name Periods
    per week    		 Credits
    L T P
    BTMT4501 Cloud Computing 3 0 0 3
    BTMT4502 Neural Networks and Deep Learning 3 0 0 3
    BTMT4601 Programme Elective – IV 3 0 0 3
    BTMT4602 Programme Elective – V 3 0 0 3
    BTMM4501 MOOC – III 0 0 0 3
    BTMP4301 Mini Project 0 0 2 1
    BTML4501 Cloud Computing Lab 0 0 2 1
    BTML4502 Neural Networks and Deep Learning Lab 0 0 2 1
    BTMI4301 Internship – II Evaluation 0 0 4 2
    TOTAL 12 0 10 20

     

    Program Elective -IV Program Elective -V
    Course
    Code    		 Course Name Course
    Code    		 Course Name
    BTMT4601a AI in Block Chain BTMT4602a Software Project Management
    BTMT4601b Sentiment Analysis BTMT4602b Health Analytics
    BTMT4601c Smart Product Development BTMT4602c Image and Video Analytics
    BTMT4601d Cyber Security BTMT4602d Business Intelligence and
    Analytics
    BTMT4601e Financial Analytics BTMT4602e Machine Learning for
    Security
  • Value Added Courses
    Course Code Course Name
    BTMA0013 Generative AI Learning Path
    BTMA0014 Big Data Technology
    BTMA0015 Certified Blockchain Developer

     

    VIII – Semester
    Course Code Course Name Periods
    per week    		 Credits
    L T P
    BTMP4302 Project Work 0 0 24 12
    BTMV4301 Comprehensive Viva-Voce 0 0 2 1
    TOTAL 0 0 26 13

PROGRAM FEE AND SCHOLARSHIPS

Fees Structure SCHOLARSHIPS ADMISSION PROCESS
Admission Fee (One-Time Fee) ₹ 6,500
1st Year ₹ 2,12,800
2nd Year ₹ 2,52,800
3rd Year ₹ 2,52,800
4th Year ₹ 2,52,800
Total Programme Fee (4 Years) ₹ 9,71,200

Scholarship is available for eligible students

Eligibility

Candidates must secure 50% in Physics, Chemistry and Mathematics of Intermediate or in the diploma course or must have appeared for Class 12 or equivalent examination with Physics, Chemistry, and Mathematics as major subjects from any recognized board. Candidates who have completed or qualified the final year of diploma in engineering courses are also eligible Candidates must not exceed the age of 24 years and the minimum age for applying is 17 years as on 31st December of Calendar Year.

EMPLOYABILITY AREAS

The IT graduates can explore the employment opportunities in various public and private sectors. They mostly acquire the following positions:

  • Hospital and Medicine
  • Game Playing
  • Speech Recognition
  • Understanding
  • Natural Language
  • Computer Vision
  • Cyber Security
  • Face Recognition
  • Transport
  • Marketing & Advertising
  • language detection machine
  • robotics