COURSE OVERVIEW

Artificial Intelligence and Data Science have shown high growth in the last few years, so The Apollo University for the B.Tech. CSE (AI & DS) students mainly focus on various courses that deal with core technologies like Machine Learning, Artificial Intelligence, Data warehouse, Data Mining, Scripting Language, Product Development and Mathematical modelling. The Students can acquire skills to perform decisions based on data analysis and gain in-depth subject knowledge on statistics, data science, computer science and logic, as data science is connected with artificial intelligence through machine learning. The students have an opportunity to become ready to fit the industry and can start their careers as data scientists and data analysts.
Programme Objectives
- To empower the students with knowledge through experiential learning.
- To provide individual attention and enable character building.
- To make students strong in data processing, data analysis and data visualisations.
- To create a conducive ambience for learning through the latest cutting-edge technologies with the collaboration of industries.
- To enhance the students’ knowledge, they need to become ready to fit as per industry needs.
Industry Leader Speak
In the twenty-first century, data science is regarded as the best career. It is simply the study of mathematics, statistics and computer science to extract information from structured and unstructured data. They are all crucial for the administration of digital data collection to be successful. The data scientist puts a lot of effort into shifting through a mountain of data to find relevant information and identify patterns and designs that can be utilised to pinpoint future goals and objectives. This demonstrates why data science matters and why data scientists are becoming more well-known and significant. Data science is now more important than ever. The reason for this is data transformation. In the past, the data was in a structured format, was compact and could be processed by straightforward BI tools.

Srinivas Middekurva
Senior Associate Consultant
Infosys
PROGRAMME HIGHLIGHTS

Programme Curriculum
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Semester - I +
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3 Week Induction Programme Course Code
Course Name
Periods per week
Credits Hours per week
L T P BTAT1701 Engineering Physics 3 1 0 4 4 BTAT1702 Engineering Mathematics 3 1 0 4 4 BTAT1801 Problem Solving and Programming with C 3 1 0 4 4 TAUT1101 University Core -I (Communicative English) 3 0 0 3 3 — University Elective I 3 0 0 3 3 BTAL1701 Engineering Physics Lab 0 0 3 1.5 3 BTAL1801 Problem Solving and Programming with C Lab 0 0 3 1.5 3 — IT Work shop 0 0 0 0 1 — Design Thinking 0 0 0 0 1 — Soft Skills 0 0 0 0 1 — Mentoring 0 0 0 0 1 — Technical Seminar 0 0 0 0 1 — Library 0 0 0 0 1 — Physical Activity 0 0 0 0 2 — Extra-curricular activities 0 0 0 0 2 — Co-curricular activity 0 0 0 0 1 — Self-Learning 0 0 0 0 1 TOTAL 15 3 6 21 36
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Semester - II +
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Course Code
Course Name
Periods per week
Credits Hours per week
L T P BTAT1703 Probability & Statistics 3 1 0 4 4 BTAT1802 Basic Electrical and Electronics Engineering 3 1 0 4 4 BTAT1301 Data Structures 3 1 0 4 4 BTAT1302 Python Programming 3 1 0 4 4 TAUT1102 University Core – II (Environmental Studies) 3 0 0 0 3 — University Elective II 3 0 0 3 3 BTAL1802 Basic Electrical and Electronics Engineering Lab 0 0 2 1 2 BTAL1301 Data Structures Lab 0 0 2 1 2 BTAL1302 Python Programming Lab 0 0 2 1 2 — Mentoring 0 0 0 0 1 — Co-curricular activity 0 0 0 0 1 — Self-Learning 0 0 0 0 1 — Physical Activity 0 0 0 0 2 — Extra-curricular activities 0 0 0 0 2 — Library 0 0 0 0 1 TOTAL 18 4 6 22 36
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Semester - III +
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Course Code
Course Name
Periods per week
Credits Hours per week
L T P BTAT2701 Discrete Mathematics and Graph Theory 3 1 0 4 4 BTAT2301 Design and Analysis of Algorithms 3 1 0 4 4 BTAT2302 Object Oriented Programming through Java 3 0 0 3 3 BTAT2801 Digital Logic design 3 0 0 3 3 TAUT2101 University Core – III (Health and Wellness) 3 0 0 3 3 — University Elective -III 3 0 0 3 3 BTAT2303 Constitution of India 3 0 0 0 3 BTAL2301 Java Programming Lab 0 0 2 1 2 BTAL2801 Digital Logic Design lab 0 0 2 1 2 — Mentoring 0 0 0 0 1 — Co-curricular activity 0 0 0 0 1 — Self-Learning 0 0 0 0 1 — Physical Activity 0 0 0 0 2 — Extra-curricular activities 0 0 0 0 2 — Soft Skills Training 0 0 0 0 1 — Certification course 0 0 0 0 1 TOTAL 22 2 6 22 36
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Semester - III +
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Course Code
Course Name
Periods per week
Credits Hours per week
L T P BTAT2307 Computer Organization and Architecture 3 1 0 4 4 BTAT2901 Management for Engineers 3 0 0 3 3 BTAT2501 Foundations of Data Science 3 0 0 3 3 BTAT2304 Database Management Systems 3 1 0 4 4 BTAT2305 Operating Systems 3 1 0 4 4 BTAT2502 Artificial Intelligence 3 0 0 3 3 BTAT2306 Universal Human Values 3 0 0 0 3 BTAL2302 Database Management Systems Lab 0 0 2 1 2 BTAL2501 Exploratory Data Analytics with R lab 0 0 2 1 2 — Internship – I * will be Evaluated in VIII- Sem
– – – – – — Mentoring 0 0 0 0 1 — Aptitude and Logical Reasoning 0 0 0 0 1 — Library 0 0 0 0 1 — Physical Activity 0 0 0 0 2 — Extra-curricular activities 0 0 0 0 2 — Technical Seminar 0 0 0 0 1 TOTAL 21 2 4 23 36
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Semester - V +
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Course Code
Course Name
Periods per week
Credits Hours per week
L T P BTAT3501 Machine Learning 3 0 0 3 3 BTAT3301 Computer Networks 3 0 0 3 3 BTAT3302 Automata and Compiler Design 3 1 0 4 4 — Faculty Elective – I 3 0 0 3 3 — Programme Elective – I 3 0 0 3 3 BTAM3501 MOOC – I 0 0 0 3 3 BTAT3303 Entrepreneurship and Start-up Management 3 0 0 0 3 BTAL3501 Machine Learning Lab 0 0 2 1 2 BTAL3301 Computer Networks Lab 0 0 2 1 2 — Mentoring 0 0 0 0 1 — Library 0 0 0 0 1 — Physical Activity 0 0 0 0 2 — Extra-curricular activities 0 0 0 0 2 — Campus Recruitment Training 0 0 0 0 4 TOTAL 18 1 8 21 36
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Semester - VI +
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Course Code
Course Name
Periods per week
Credits Hours per week
L T P BTAT3502 Natural Language Processing 3 0 0 3 3 BTAT3503 Data Warehousing and Mining 3 0 0 3 3 — Faculty Elective – II 3 0 0 3 3 — Programme Elective – II 3 0 0 3 3 — Programme Elective – III 3 0 0 3 3 BTAM3502 MOOC – II 0 0 0 3 3 BTAL3502 Natural Language Processing lab 0 0 2 1 2 BTAL3503 Data Warehousing and Mining lab 0 0 2 1 2 — Internship – II* will be Evaluated in VIII -Sem – – – – – — Mentoring 0 0 0 0 1 — Library 0 0 0 0 1 — Physical Activity 0 0 0 0 2 — Extra-curricular activities 0 0 0 0 2 — Valued added courses 0 0 0 0 2 — Seminar 0 0 0 0 1 — Technical Training 0 0 0 0 3 — Self-Learning 0 0 0 0 2 TOTAL 15 0 4 20 36 Faculty Elective -II Course Code Course Name Course Code Course Name SOTT3402a Design Patterns SOTT3402q Embedded Systems SOTT3402b Cyber Security SOTT3402r Green Computing SOTT3402c Software Project management SOTT3402s Cloud Security SOTT3402d Agile Software Development SOTT3402t DevNet SOTT3402e Cloud Computing SOTT3402u Advanced computer networks SOTT3402f Mobile Computing SOTT3402v Network Security SOTT3402g Image Processing SOTT3402w Fault Tolerant Systems SOTT3402h Deep learning SOTT3402x Computational Intelligence SOTT3402i E-Commerce SOTT3402y Data Analytics with Tableau SOTT3402j
Block Chain Technology SOTT3402z Human Computer Interaction SOTT3402k
Mathematical Foundations of Data Science SOTT3402l
Transforms and Boundary Value Problems SOTT3402m Optimization Techniques SOTT3402n Information Security SOTT3402o Ethical Hacking SOTT3402p Internet of Things Program Elective -II Course Code Course Name BTAT3602a Image Processing BTAT3602b Cryptography & Network security BTAT3602c Deep Learning BTAT3602d Distributed Databases BTAT3602e Explainable Artificial Intelligence Program Elective -III Course Code Course Name BTAT3603a High Performance Computing BTAT3603b Generative AI BTAT3603c MERN Technologies BTAT3603d Network Programming BTAT3603e Software Requirements Management Value Added Courses Course Code Course Name BTAA0009 Data Analyst Learning Path BTAA0010 BDA Foundation BTAA0011 Blockchain Essentials BTAA0012 Oracle Cloud Operations Engineer
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Semester - VII +
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Course Code
Course Name
Periods per week
Credits Hours per week
L T P BTAT4501 Big Data Analytics 3 0 0 3 3 BTAT4502 Neural Networks and Deep Learning 3 0 0 3 3 — Programme Elective – IV 3 0 0 3 3 — Programme Elective – V 3 0 0 3 3 BTAM4501 MOOC – III 0 0 0 3 3 BTAP4501 Mini Project 0 0 2 1 2 BTAL4501 Big data Analytics lab 0 0 2 1 2 BTAL4502 Neural Networks and Deep Learning lab 0 0 2 1 2 — Mentoring 0 0 0 0 1 — Library 0 0 0 0 1 — Physical Activity 0 0 0 0 2 — Extra-curricular activities 0 0 0 0 2 — Valued added courses 0 0 0 0 1 — Seminar 0 0 0 0 1 — Technical Training 0 0 0 0 6 — Technical Paper Writing 0 0 0 0 1 TOTAL 12 0 10 20 36 Program Elective -IV Course Code Course Name BTAT4601a Social Network Analysis BTAT4601b AI in Block Chain BTAT4601c Malware Analysis in Data Science BTAT4601d Social Media Analytics BTAT4601e Financial Analytics Program Elective -V Course Code Course Name BTAT4602a Software Project Management BTAT4602b Health Analytics BTAT4602c Image and Video Analytics BTAT4602d Business Intelligence and Analytics BTAT4602e Machine Learning for Security Value Added Courses Course Code Course Name BTAA0013 BI and Analytics with Looker BTAA0014 Big Data Technology BTAA0015 Certified Blockchain Developer
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Semester - VIII +
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Course Code Course Name
Periods per week
Credits Hours per week
L T P BTAP4502 Project Work 0 0 24 12 24 BTAI3501 Internship-I Evaluation# 0 0 0 2 0 BTAI4501 Internship – II Evaluation# 0 0 0 2 0 TOTAL 0 0 24 16 24
PROGRAMME FEE AND SCHOLARSHIPS
One-Time Fee | Admission Fee | ₹ 7,000 |
1st Year | Tuition Fee + Annual Recurring Fee | ₹ 2,50,000 + ₹ 13,000 |
2nd Year | Tuition Fee + Annual Recurring Fee | ₹ 2,50,000 + ₹ 13,000 |
3rd Year | Tuition Fee + Annual Recurring Fee | ₹ 2,50,000 + ₹ 13,000 |
4th Year | Tuition Fee + Annual Recurring Fee | ₹ 2,50,000 + ₹ 13,000 |
Total Course Fee | ₹ 10,59,000 |
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 Duration | You Will Join In | Seats Available | Education Qualification |
---|---|---|---|
3 Years | 2nd Year | 6 | A 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
IT graduates can explore employment opportunities in various public and private sectors. They mostly acquire the following positions:

- Data Scientist
- Machine Learning Engineer
- Robotics Scientist
- AI Data Analyst
- AI Engineer
- Business Intelligence Developer