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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 CodeCourse NamePeriods
    per week    		Credits
    LTP
    BTMT1701Engineering Physics3104
    BTMT1702Engineering Mathematics3104
    BTMT1801Problem Solving and Programming with C3104
    BTMT1101Communicative English3003
    BTMT1201University Elective I3003
    BTML1701Engineering Physics Lab0031.5
    BTML1801Problem Solving and Programming with C
    Lab    		0031.5
    TOTAL153621
  • Course CodeCourse NamePeriods
    per week    		Credits
    LTP
    BTMT1703Probability & Statistics3104
    BTMT1802Basic Electrical and Electronics Engineering3104
    BTMT1301Data Structures3104
    BTMT1302Python Programming3104
    BTMT1102Environmental Studies3000
    BTMT1202University Elective II3003
    BTML1802Basic Electrical and Electronics Engineering
    Lab    		0021
    BTML1301Data Structures Lab0021
    BTML1302Python Programming Lab0021
    TOTAL184622
  • Course CodeCourse NamePeriods
    per week    		Credits
    LTP
    BTMT2701Discrete Mathematics and Graph Theory3104
    BTMT2301Design and Analysis of Algorithms3104
    BTMT2302Object Oriented Programming through Java3003
    BTMT2801Digital Logic design3003
    University Core – III3003
    University Elective -III3003
    BTMT2303Constitution of India3000
    BTML2301Java Programming Lab0021
    BTML2801Digital Logic Design lab0021
    TOTAL212422
  • Course CodeCourse NamePeriods
    per week    		Credits
    LTP
    BTMT2702Deterministic     Stochastic     and     Statistical
    Methods    		3104
    BTMT2901Management for Engineers3003
    BTMT2501Artificial Intelligence3003
    BTMT2304Database Management Systems3003
    BTMT2305Operating Systems3104
    BTMT2502Machine Learning3003
    BTMT2306Universal Human Values3000
    BTML2302Database Management Systems Lab0021
    BTML2501Machine Learning Lab0021
    —Internship – I will be Evaluated in V Sem––––
    TOTAL212422
  • Value Added Courses
    Course CodeCourse Name
    BTMA0001Getting Started with Google Cloud Learning Path
    BTMA0002Fundamentals of Data Analytics
    BTMA0003Introduction to Blockchain Technology
    BTMA0004Oracle Cloud Infrastructure Architect

     

    V – Semester
    Course CodeCourse NamePeriods
    per week    		Credits
    LTP
    BTMT3301Computer Networks3003
    BTMT3302Automata and Compiler Design3104
    BTMT3501Data Analysis and Visualization3003
    BTMT3401Faculty Elective – I3003
    BTMT3601Programme Elective – I3003
    BTMM3501MOOC – I0003
    BTML3501Computer Networks Lab0021
    BTML3502Data Visualization Lab0021
    BTMI3301Internship-I Evaluation0042
    TOTAL151823

     

    Faculty Elective -IProgram Elective -I
    Course CodeCourse NameCourse
    Code    		Course Name
    BTMT3401aObject Oriented Analysis and
    Design    		BTMT3601aSoftware Engineering
    BTMT3401bSoftware EngineeringBTMT3601bApplications of AI
    BTMT3401cArtificial IntelligenceBTMT3601cDigital Marketing Analytics
    BTMT3401dComputer Organisation and
    Architecture    		BTMT3601dIntelligent Multi Agent and Expert System
    BTMT3401eSoftware EngineeringBTMT3601eMachine Learning
    Operations
    BTMT3401fAdvanced Data Structures
    BTMT3401gData Warehousing and Mining
    BTMT3401hMachine Learning
    BTMT3401iDifferential Equations and Vector
    Calculus
    BTMT3401jNumerical Methods for Engineers
    BTMT3401kMathematical Foundations of Cyber
    Security
    BTMT3401lInformation Retrieval Systems
    BTMT3401mCryptography and Network
    Security
    BTMT3401nPrinciples of Programming
    Languages
    BTMT3401oUnix and Shell Programming
    BTMT3401pIntroduction to Psychology
    BTMT3401qIndustry 4.0
    BTMT3401rComputer Vision
  • Value Added Courses
    Course CodeCourse Name
    BTMA0005Database Engineer Learning Path
    BTMA0006Big Data Foundation Course
    BTMA0007Programming Basics for Blockchain Engineers
    BTMA0008Oracle Cloud Security Administrator

     

    VI – Semester
    Course CodeCourse NamePeriods
    per week    		Credits
    LTP
    BTMT3502Natural Language Processing3003
    BTMT3503Advanced Machine Learning3003
    BTMT3402Faculty Elective – III3003
    BTMT3602Programme Elective – II3003
    BTMT3603Programme Elective – III3003
    BTMM3502MOOC – II0003
    BTML3503Natural Language Processing Lab0021
    BTML3504Advanced Machine Learning Lab0021
    —Internship – II will be Evaluated in VII Sem
    TOTAL150420

     

    Faculty Elective -IIProgram Elective -II
    Course CodeCourse NameCourse CodeCourse Name
    BTMT3402aDesign PatternsBTMT3602aMachine Intelligence for Medical
    Images
    BTMT3402bCyber SecurityBTMT3602bEvolutionary Computation and
    Opinion Mining
    BTMT3402cSoftware Project
    management    		BTMT3602cPractical Machine Learning with
    TensorFlow
    BTMT3402dLinux ProgrammingBTMT3602dCryptography and Network Security
    BTMT3402eCloud ComputingBTMT3602eAI for Robotics
    BTMT3402fMobile ComputingProgram Elective -III
    BTMT3402gImage ProcessingBTMT3603aSoftware Testing Methodologies
    BTMT3402hDeep LearningBTMT3603bAI& ML in Health Care
    BTMT3402iE-CommerceBTMT3603cHuman Machine Interaction
    BTMT3402jBlock Chain TechnologyBTMT3603dPredictive Analytics
    BTMT3402kMathematical Foundations of
    Data Science    		BTMT3603eNature Inspired Algorithms
    BTMT3402lTransforms and Boundary
    Value Problems
    BTMT3402mOptimization Techniques
    BTMT3402nInformation Security
    BTMT3402oEthical Hacking
    BTMT3402pInternet of Things
    BTMT3402qEmbedded Systems
    BTMT3402rGreen Computing
    BTMT3402sCloud Security
    BTMT3402tDevNet
    BTMT3402uAdvanced Computer
    Networks
    BTMT3402vNetwork Security
    BTMT3402wFault Tolerant Systems
    BTMT3402xComputational Intelligence
    BTMT3402yData Analytics with Tableau
  • Value Added Courses
    Course CodeCourse Name
    BTMA0009Machine Learning Engineer Learning Path
    BTMA0010BDA Foundation
    BTMA0011Blockchain Essentials
    BTMA0012Oracle Cloud Operations Engineer

     

    VII – Semester
    Course CodeCourse NamePeriods
    per week    		Credits
    LTP
    BTMT4501Cloud Computing3003
    BTMT4502Neural Networks and Deep Learning3003
    BTMT4601Programme Elective – IV3003
    BTMT4602Programme Elective – V3003
    BTMM4501MOOC – III0003
    BTMP4301Mini Project0021
    BTML4501Cloud Computing Lab0021
    BTML4502Neural Networks and Deep Learning Lab0021
    BTMI4301Internship – II Evaluation0042
    TOTAL1201020

     

    Program Elective -IVProgram Elective -V
    Course
    Code    		Course NameCourse
    Code    		Course Name
    BTMT4601aAI in Block ChainBTMT4602aSoftware Project Management
    BTMT4601bSentiment AnalysisBTMT4602bHealth Analytics
    BTMT4601cSmart Product DevelopmentBTMT4602cImage and Video Analytics
    BTMT4601dCyber SecurityBTMT4602dBusiness Intelligence and
    Analytics
    BTMT4601eFinancial AnalyticsBTMT4602eMachine Learning for
    Security
  • Value Added Courses
    Course CodeCourse Name
    BTMA0013Generative AI Learning Path
    BTMA0014Big Data Technology
    BTMA0015Certified Blockchain Developer

     

    VIII – Semester
    Course CodeCourse NamePeriods
    per week    		Credits
    LTP
    BTMP4302Project Work002412
    BTMV4301Comprehensive Viva-Voce0021
    TOTAL002613

PROGRAM FEE AND SCHOLARSHIPS

Fees Structure SCHOLARSHIPS ADMISSION PROCESS
Admission Fee (One-Time Fee)₹ 13,000
1st Year₹ 2,35,000
2nd Year₹ 2,35,000
3rd Year₹ 2,35,000
4th Year₹ 2,35,000
Total Programme Fee (4 Years)₹ 9,53,000

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.

Lateral Entry

Total Course DurationYou Will Join InSeats AvailableEducation Qualification
3 Years2nd Year6A three-year engineering diploma in Computer Science program from a recognized institute. The candidateso must have secured at least 50% marks in their diploma program.

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