B.Sc. (Hons.) Mathematics- Data Science

DETAILS

B.Sc. (Hons) Mathematics with specialization in 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. 

Duration of Program

3 years (6 semesters)

Seats

10*

DESIGN YOUR OWN DEGREE


upes

UPES’ curriculum framework is holistic in its overall structure and yet focuses on the individual need of the student to discover, experience, explore and challenge. Along with the core subject, students have the option to choose from subject-focused specialisations. They are also allowed to choose minor/exploratory subject from other schools at UPES that are: School of Engineering, School of Computer Science, School of Law, School of Business, School of Health Sciences, School of Design, School of Modern Media, and School of Liberal Studies.

Further, based on the multifaceted needs of the global workplace and evolving lifestyles, the curriculum offers Signature and Life-Skills courses through School for Life. To round off this learning experience, students are required to do mandatory internships in the social sector, government/public sector, and industry. The combinations available for students to pick and choose from are endless, ensuring both depth and width of knowledge.

DETAILS

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

SEMESTER I

 

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

 

  

SEMESTER II

 

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

 

  

SEMESTER III

 

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

 

  

SEMESTER IV

 

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

 

  

SEMESTER V

 

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

 

  

SEMESTER VI

 

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

 

 

SPECIALISATION

 

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 

 

DETAILS

Program Educational Objectives (PEOs)

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. 

Program Specific Outcomes (PSOs)

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 

Career Prospects
  • 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 
Eligibility

Minimum 50% marks in Classes X and XII.(PCM/B)

Entrance Test

Personal Interview

Curriculum

SEMESTER I

 

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

 

  

SEMESTER II

 

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

 

  

SEMESTER III

 

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

 

  

SEMESTER IV

 

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

 

  

SEMESTER V

 

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

 

  

SEMESTER VI

 

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

 

 

SPECIALISATION

 

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

 

Innovative Teaching and Learning

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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