Duration of Program 3 years (6 semesters)


Seats 15*

*Total Seats in B.Sc. (Hons.) Chemistry

Data Science is a blend of various tools, algorithms, and machine learning principles with the goal to discover hidden patterns from the raw data. Data Scientist not only does the exploratory analysis to discover insights from it, but also uses various advanced machine-learning algorithms to identify the occurrence of a particular event in the future. Data Science is primarily used to make decisions and predictions making use of predictive causal analytics, prescriptive analytics (predictive plus decision science) and machine learning. 


The foundation of higher learning at UPES since its inception has been to explore and promote areas of learning that are innovative and future focused. This has led to constant evolution in facilitating creative and collaborative learning engagements for students through realignment of curriculum and exploration of virtual tools, and open-source courseware; thereby creating borderless learning and access to limitless information.

The new curriculum framework at UPES, ABLE (Academic Blueprint for Learning Excellence) is holistic in its overall structure and yet focuses on the individual need of the student to discover, experience, explore and challenge. The learning is segmented into core subject studies, core specialism studies, minors/exploratory subjects, and signature and life skills learning. The latter three are offered by the newly-instituted School for Life.

SFL (School for Life) is an intrinsic part of the composite UPES student experience and facilitates learning and education that is a balance between what students want, and what is needed of them as future global citizens and leaders of tomorrow. With courses designed to equip students with lifelong learning skills, a focus on a wide range of contemporary issues, and a mandatory social and professional internship experience that is unique, UPES believes in igniting to inspire the best version within an individual to better the world.


PEO-1: Graduate will have significant opportunities to get employment at Local and National level, and can work as analyst, quality controller, research assistant and in government sector job. 

PEO-2: Graduate will have leadership quality to handle all kind of circumstances in diversities by providing interdisciplinary and multidisciplinary learning environment. 

PEO-3: Graduate will continuously learn and adopt new skills and techniques to overcome the problem related with new technologies. 

PEO-4: Graduate will be able to formulate, investigate and analyze scientifically real life problems along with ethical attitude which works in multidisciplinary team. 

PSO-1: Understand the mathematical concepts in the field of algebra, analysis, computational techniques, optimization, differential equations, etc. 

PSO-2: Able to acquire critical thinking and effective reasoning skills for establishing mathematical results and to provide a knowledge base for advanced study or research in Mathematics. 

PSO-3: Execute new ideas in the field of research and development using principles of Mathematics learned through activities such as expert lecturers, workshops, seminars and field projects 

  • Lecturer/Assistant Professor,  
  • Mathematician,  
  • Software Developer,  
  • Data Analyst, Business Analyst,  
  • Risk and finance management,  
  • Weather derivative and Insurance,  
  • Mathematical Modeler,  
  • Quantitative Developer,  
  • Statistical officer,  
  • Statistician,  
  • Researcher and Demographer 
Minimum 50% marks in Classes X and XII.(PCM/B)
Personal Interview



Category Subject Code Subject Credits
Core Course    Differential Calculus  4
Core Course    Differential Calculus  Lab 1
Core Course    Algebra 5
Core Course  HSFS 1003 Environmental Science 2
Generic Elective    Generic Elective - I (Physics/Chemistry/Geology) 6
School for life SLLS0101 Learning how to learn 2
School for life SLLS0102 Living Conversation 2
    Total 22





Category Subject Code Subject Credits
Core Course – III   Real Analysis-I 5
Core Course – IV   Integral calculus 4
    Integral calculus Lab 1
Core Course – V   Linear algebra 5
Generic Elective    Generic Elective-II (Physics/Chemistry/Geology) 6
School for life SLLS0103 Leadership & Teamwork 2
School for life SLLG0104 Critical Thinking & Writing 3
    Total 26





Category Subject Code Subject Credits
Core Course    Analytical Geometry 5
Core Course    Ordinary Differential Equations 4
Core Course    Ordinary Differential Equations Lab 1
Core Course    Complex analysis 5
Skill Enhancement    Skill Enhancement Electives I 2
Generic Elective   Generic Elective-III (Physics/Chemistry/Geology) 6
School for life SLLS 0201 Design Thinking 2
School for life SLLS 2001 Social Internship 0
    Total 25





Category Subject Code Subject Credits
Core Course    Function of several variable & PDE 4
Core Course    Function of several variable & PDE Lab 1
Core Course    Real analysis- II 5
Core Course    Probability and Statistics 5
Skill Enhancement   Skill Enhancement Electives II 2
Generic Elective    Generic Elective-IV (Physics/Chemistry/Geology) 6
School for life   Working with Data 2
School for life   Ethical Leadership in the 21th Century (Human Values and Ethics) 3
    Total 28





Category Subject Code Subject Credits
Core Course    Advanced Algebra 5
Core Course   Linear and Non Linear Programming  5
Specialization course   Specialization course I  5
Specialization course   Specialization course II 5
School for life   Persuasive Presence 2
School for life   Environment and Sustainability - Himalaya Fellowship 3
    Total 25





Category Subject Code Subject Credits
Core Course    Mathematical Methods 4
Core Course    Mathematical Methods Lab 1
Specialization course    Specialization course III  5
Specialization course   Specialization course IV  5
School for life   Signature course 5 3
Dissertation   Dissertation 6
    Total 24





Specialization Course I
Bayesian Data Analysis
Specialization Course II
Financial Data Analysis
Specialization Course III (Any One)
Big Data handling with Hadoop and Spark
Time Series and Forecasting Methods
Specialization Course IV (Any One)
Multivariate Statistics
Text Analytics


We at the department believe in experiential teaching and learning and strive to imbibe problem solving skills and critical thinking in the students. The following practices are in place to improve the quality of Teaching-Learning and student experience: 

  • Design and Review of individual Course Plans at the beginning of session 
  • Course Completion Report (CCR) 
  • Academic Planning & Monitoring 
  • Quality Laboratory Experience 
  • Encouraging Advanced Learner 
  • Slow Learners Support 
  • ICT enabled Classroom (sound system, mic and projector) 
  • Guest lectures  
  • Certification Courses  
  • Professional Software Training (PST) and Certification 
  • NPTEL lectures 
  • Use of Virtual labs 
  • Participation in competitive events (In-house/National/International). 
  • Participation in Conferences/Seminars/Workshops (National/International). 
  • Semester Exchange Program. 
  • FDP 


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