About the Program

The Five-year Integrated M.Sc. Program on Data Science is intended for the students who aspire to excel in data science. It provides a spectrum of basics to advanced mathematical methods and their applications to both conventional and IT industries that enable to tackle emerging problems. The curriculum covers the necessary basics in Mathematics, Statistics, Computer programming and Business analytics and it also includes the emerging topics such as Big Data Analytics, Neural Networks, Machine Learning, Artificial Intelligence, Data Visualization, and Data Modeling to deal with vast data from business, healthcare, sensors, Internet, surveys, social media, astronomy, human space exploration and operations, and aeronautics.

In addition to the regular curriculum, students are encouraged to take up summer/winter In-plant training/Internship. This will help students to gain real time processing of data by doing Prediction analysis, Pattern Recognition, Anomaly Detection, Clustering, Actionable Insights, Automated Processes and decision making, Segmentation, Optimization and Forecasting. A full length project is included in the curriculum to be completed in the final semester. Students are expected to take up such projects in industries. This helps students to gain knowledge on working conditions and industrial requirements when they are employed.

Harvard was right about data scientists. It’s an extremely important and high-demand role that can have significant impact on a business’ ability to achieve its goals, whether they are financial, operational, strategic, and so on.

  • Salient Features of the Program
    • Gain knowledge in Mathematics, Computer Programming and Business Analytics.
    • Placements in both conventional and software Industries.
    • Scope for doing research for those who aim to be a teacher, scientist or research associate in highly reputed national and international institutions.
    • One of the most wanted program in academics and industry.

Curriculum and syllabi

Data Science curriculum is carefully designed to cater the industrial needs and it includes Mathematics, Computer Science and Business Analytics. The syllabus starts with the basics in Calculus, Mathematical Logic, Probability, Statistics, Linear Algebra, Data Management and Analytics to advanced topics like Neural Networks, Artificial Intelligence, Machine Learning, Data Modeling and Big Data.

Program Outcomes

  • Knowledge in Mathematics and Computer Science: Understand the basic concepts, fundamental principles and the scientific theories related to Data Science.
  • Abstract thinking: Ability to absorb and understand the abstract concepts that lead to various advanced theories in Mathematics, Statistics and Computer science.
  • Modelling and solving: Ability in modelling and solving problems by identifying and employing the appropriate existing theories and methods.
  • Advanced theories and methods: Understand advanced theories and methods to design solutions for complex data science problems.
  • Applications in Engineering and Sciences: Understand the role of mathematical sciences and apply the same to solve the real life problems in fields of data science.
  • Modern software tool usage: Acquire the skills in handling scientific tools towards problem solving and solution analysis.
  • Environment and sustainability: Understand the significance of preserving the environment towards sustainable development.
  • Ethics: Imbibe ethical, moral and social values in personal and social life leading to highly cultured and civilized personality. Continue to enhance the knowledge and skills in mathematics and computer science for constructive activities, and demonstrate highest standards of professional ethics.
  • Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
  • Communication: Develop various communication skills such as reading, listening, and speaking which will help in expressing ideas and views clearly and effectively.
  • Project management and Research: Demonstrate knowledge, understand the scientific and management principles and apply these to one’s own work, as a member/ leader in a team to manage projects and multidisciplinary research environments. Also use the research-based knowledge to analyse and solve advanced problems in data science.
  • 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.

Job opportunities:

Employment opportunities for students with Data Science degree are plenty in the job market. The need for Data Scientists is growing every day in all fields. Harvard calls the Data Scientist job as the Sexiest job of 21st Century. They are also eligible to work as Scientists and Research Associates in highly reputed organizations such as ISRO, DRDO and CSIR. In addition, lucrative jobs are available in software industries. The prospective recruiters for the students of Integrated Data Science are:

Search Engine Companies

Social Network Companies

Engineering Related Companies

Financial Related Companies

Data Science Vendors

The other few companies offering data scientist jobs are

* More than 8000 companies hiring data scientist.

Curriculum

Semester 1
Course Code Course Title L T P Cr
18ENG101 Communicative English 2 0 2 3
HUM Language Paper I 1 0 2 2
18MAT101 Calculus 3 1 0 4
18MAT104 Linear Algebra 3 0 2 4
18PHY101 Physics 3 0 0 3
18CSA100 Problem Solving and Computer Programming 3 0 0 3
18CSA180 Problem solving computer Lab. 0 0 2 1
18PHY181 Physics Lab. 0 0 2 1
18CUL101 Cultural Education I 2 0 0 2
  Total   23
Semester 2
Course Code Course Title L T P Cr
18ENG121 Professional Communication 1 0 2 2
HUM Language Paper II 1 0 2 2
18MAT115 Vector Analysis 3 1 0 4
18MAT112 Discrete Mathematics 3 0 2 4
18CSA116 Advanced Computer Programming 3 0 0 3
18CSA117 Digital Electronics 3 0 0 3
18CSA181 Advanced Computer Programming Lab. 0 0 2 1
18CSA185 Digital Electronics Lab 0 0 2 1
18CUL111 Cultural Education II 2 0 0 2
  Total   22
Semester 3
Course Code Course Title L T P Cr
CSE Data Structures 3 1 0 4
MAT Differential Equations 3 1 0 4
MAT Probability and Statistics 3 1 0 4
MAT Numerical Methods 3 1 0 4
CSE Fundamentals Of Data science 3 1 0 4
HUM Environmental Science and Sustainability 3 0 0 3
MAT Data science Lab 1 :Statistics and Numerical Lab 0 0 2 1
HUM Amrita Values Programme I 1 0 0 1
CSE Data Structures lab 0 0 2 1
       
  Total   26
Semester 4
Course Code Course Title L T P Cr
MAT Statistical Inference Theory for Data science 3 0 0 3
MAT Introdcution to Modern Algebra 3 0 0 3
CSE Formal Languages and Automata Theory 3 1 0 4
CSE Design and Analysis of Algorithms 3 1 0 4
CSE Software Engineering 3 1 0 4
HUM Open Elective A* 3 0 0 3
MAT Data Science Lab-II: Inference Theory 0 0 2 1
  Life Skills I 1 0 2 2
CSE Algorithm Lab 0 0 2 1
HUM Amrita Values Programme II 1 0 0 1
  Total   26
Semester 5
Course Code Course Title L T P Cr
CSE Operating Systems 3 0 0 3
MAT Transfrom Technique 3 1 0 4
CYB Number Theory and Information Security 3 1 0 4
MAT Operations Research 3 1 0 4
CSE Database Management Systems 3 1 0 4
HUM Live-in-Lab.@ / Open Elective B* 3 0 0 3
  Life Skills II 1 0 2 2
MAT DBMS Lab 0 0 2 1
CSE Open Lab-I (JAVA/R programming/Azure...) 0 0 2 1
  Total   26
Semester 6
Course Code Course Title L T P Cr
MAT Graph Analytics and Algorithms 3 0 2 4
MAT Regression Analysis for Data science 3 1 0 4
CSE Soft Computing 3 1 0 4
CSE Data Visualization 3 1 0 4
CSE Data Base Design 3 1 0 4
CSE Soft Computing-Lab 0 0 2 1
CSE Open Lab II (Algorithms.io /Hadoop/ Cascading...,) 0 0 2 1
  Life Skills III 1 0 2 2
       
  Total   24
Semester 7
Course Code Course Title L T P Cr
CSE Parallel and Distributed Computing 3 0 2 4
CEN Machine Learning for Data Science 3 0 2 4
CSE Big Data Analytics 3 0 2 4
CSE Artificial Intelligence 3 0 0 3
CYB Data Security 3 0 0 3
MAT/CSE Elective I 3 0 0 3
MAT/CSE Elective II 3 0 0 3
  Total   26
Semester 8
Course Code Course Title L T P Cr
  Project –I (Internship in Industries)   10
       
       
       
       
       
       
  Total   10
Semester 9
Course Code Course Title L T P Cr
MAT/CSE Statistical Pattern Recognition 3 0 2 4
CEN Natural Language Processing for Data 3 0 2 4
MAT/CSE Elective III 3 0 0 3
MAT/CSE Elective IV 3 0 0 3
  Mini project   5
  Total   19
Semester 10
Course Code Course Title L T P Cr
MAT/CSE Elective V 3 0 0 3
MAT/CSE Elective VI 3 0 0 3
       
       
  Project-II (Research based) Dissertation   12
  Total   18
Total Credits of all Semesters 220
Mathematics Stream
Advanced Algebra 3 0 0 3
Data Analytics in Biology 3 0 0 3
Advanced Optimization 3 0 0 3
Time Series Analysis 3 0 0 3
Stochastic Processes and Simulation 3 0 0 3
Wavelet Analysis 3 0 0 3
Queuing Theory and Inventory Control Theory 3 0 0 3
Theory of Sampling and Design of Experiments 3 0 0 3
Computational Financial Mathematics 3 0 0 3
Chemical Informatics 3 0 0 3
Computer Science Stream
Deep Learning 3 0 0 3
Cryptography 3 0 0 3
Data Analytics for Business Applications 3 0 0 3
Image Processing 3 0 0 3
Intelligent Systems 3 0 0 3
Categorical Data Analysis 3 0 0 3
Data Compression 3 0 0 3
Big Data Storage and Analysis 3 0 0 3
IoT 3 0 0 3
Introduction to Embedded Systems 3 0 0 3
You can join this program at
Degree: 
Integrated Degree
School: 
School of Arts and Sciences
Campuses: 
Coimbatore