Data Science & Analytics

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Program Educational
Objectives

The PEOs of the program are:

  1. To develop students’ in depth understanding of the key technologies in data science: data mining, machine learning, visualization techniques and statistics.
  2. To prepare students to practice problem analysis and decision-making.
  3. To prepare students to gain practical, hands-on experience with statistics programming languages and big data tools.

Program Learning
Outcomes

Upon completion of the degree program, students will be able to:

  1. Apply quantitative modeling and data analysis techniques to solve real world business problems, communicate findings, and effectively present results using data visualization techniques.
  2. Recognize and analyze ethical issues in business related to intellectual property, data security, integrity, and privacy.
  3. Apply ethical practices in everyday business activities and make well-reasoned ethical business and data management decisions.
  4. Demonstrate knowledge of statistical data analysis techniques utilized in business decision making.
  5. Apply principles of Data Science to the analysis of business problems.
  6. Use data mining software to solve real-world problems.
  7. Employ cutting edge tools and technologies to analyze Big Data.
  8. Apply algorithms to build machine intelligence.

Employment
Scope

  1. Business Analyst
  2. Business Intelligence Analyst
  3. SAS Data Analyst
  4. IBM Data Analyst
  5. Data Scientist
  6. Data Mining Engineer
  7. Machine Learning Engineer
  8. Big Data Scientist

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Courses

cyber-security-cyber-law
Cyber Security & Cyber Law
data-science-analytics
Data Science & Analytics
software-technologies
Software Technologies

PG Programs

Activities

Teaching Scheme

Semester I
Subject Code Subject Name Elaboration Teaching Scheme (Hours) Credits Evaluation Scheme
Theory Marks Practical Marks Total Marks
Theory Practical Tutorial ESE (E) IA CSE Viva (V) Term Work  (TW)
05DS0101 Applied Mathematics CORE (Primary) 4 0 2 6 60 20 20 0 0 100
05DS0102 OOP Using Python 3 4 0 5 60 20 20 25 25 150
05DS0103 Operating System Concepts 3 4 0 5 60 20 20 25 25 150
05DS0104 Data Analytics with R Specialization 1 4 4 0 6 60 20 20 25 25 150
05DS0105 Data Warehousing Fundamentals Specialization 2 4 4 0 6 60 20 20 25 25 150
05DS0106 Library & Information Resources Data & Information Skills (Tertiary) 0 2 0 1 0 0 0 0 0 0
05DS0107 Sports & Yoga Physical Education (Tertiary) 0 2 0 1 0 0 0 0 0 0
Total : 18 20 2 30           700
Semester II
Subject Code Subject Name Elaboration Teaching Scheme (Hours) Credits Evaluation Scheme
Theory Marks Practical Marks Total Marks
Theory Practical Tutorial ESE (E) IA CSE Viva (V) Term Work  (TW)
05DS0201 Advanced Data Structures CORE (Primary) 4 4 0 6 60 20 20 25 25 150
05DS0202 Advanced Computer Networks 4 2 0 5 60 20 20 25 25 150
05DS0203 Artificial Intelligence 4 4 0 6 60 20 20 25 25 150
05DS0204 Big Data Tools Specialization 1 4 4 0 6 60 20 20 25 25 150
05DS0205 Big Data Mining Specialization 2 4 2 0 5 60 20 20 25 25 150
05DS0206 Library & Information Resources Data & Information Skills (Tertiary) 0 2 0 1 0 0 0 0 0 0
05DS0207 Sports & Yoga Physical Education (Tertiary) 0 2 0 1 0 0 0 0 0 0
Total : 20 20 0 30           750
Semester III
Subject Code Subject Name Elaboration Teaching Scheme (Hours) Credits Evaluation Scheme
Theory Marks Practical Marks Total Marks
Theory Practical Tutorial ESE (E) IA CSE Viva (V) Term Work  (TW)
05DS0301 Cloud Computing CORE (Primary) 4 4 0 6 60 20 20 25 25 150
05DS0302 Software Project Management 4 0 0 4 60 20 20 0 0 100
05DS0303 Machine Learning 4 4 0 6 60 20 20 25 25 150
05DS0304 Elective – 1 Specialization 1 4 4 0 6 60 20 20 25 25 150
05DS0305 Elective – 2 Specialization 2 4 4 0 6 60 20 20 25 25 150
05DS0306 Library & Information Resources Data & Information Skills (Tertiary) 0 2 0 1 0 0 0 0 0 0
05DS0307 Sports & Yoga Physical Education (Tertiary) 0 2 0 1 0 0 0 0 0 0
Total : 20 20 0 30           700

*Electives;

  1. Computer Vision & Image Processing
  2. Pattern-Oriented Architecture
  3. Agile Methods
  4. Mobile Application Development
  5. Social Network Analysis
Semester IV
Subject Code Subject Name Elaboration Teaching Scheme (Hours) Credits Evaluation Scheme
Theory Marks Practical Marks Total Marks
Theory Practical Tutorial ESE (E) IA CSE Viva (V) Term Work  (TW)
05DS0401 User Defined Project/Industry Define Project Industry Internship 30 250 100 350
Total :       30           350