Bachelor of science in Mathematics, Statistics and Data Science provides a strong theoretical foundation of mathematics and Statistics needed for Data Science applications.
Data science is an emerging field and finds its applications in vast number of areas such as Big Data Analysis, Data and Information Visualisation, Machine Learning, Statistical Analysis, Finance and Data Mining.
After successful completion of the course, the students can find job opportunities as Data Scientist and Data Analyst in most of the MNCs and Oranisations dealing with Big Data Analysis.
| Overview of Bachelor of Science in Mathematics, Statistics and Data Science: | |
|---|---|
| Course Level | Graduate |
| Awarding Body | Osmania university |
| Duration | 3 years |
| Examination Type | Semester System |
| Eligibility | Pass in 12th class from CBSE / ICSE Stream or Intermediate, HSC
Candidate who passed any Diploma course through Polytechnic of Telangana State.
A candidate who have passed any other exam which is considered equivalent by the Board of Intermediate Education – Hyderabad
|
| Examination |
All evaluations are conducted as per the norm of Osmania University. These are two components of evaluations:
Internal – 20 Marks
External – 80 Marks
There will be 2 internal examinations during the semester as per the schedule of Osmania University. At the end of each semester, final external examination will be conducted by Osmania University
|
| S-No | SEM - I | Credits |
|---|---|---|
| 1 | English | 4 |
| 2 | Second Language | 4 |
| 3 |
a) Environmental Science(aecc1)
b) Basic Computer Skills(aecc1)
|
2 |
| 4 | Differential and Integral Calculus | 5 |
| 5 | Descriptive Statistics And Probability | 5 |
| 6 | Fundamentals Of Information Technology | 5 |
| S-No | SEM - II | Credits |
|---|---|---|
| 1 | English | 4 |
| 2 | Second Language | 4 |
| 3 |
a) Environmental Science(aecc2)
b) Basic Computer Skills(aecc2)
|
2 |
| 4 | Differential Equations | 5 |
| 5 | Probability Distributions | 5 |
| 6 | Problem Solving And Python Programming | 5 |
| S no | SEM - III | Credits |
|---|---|---|
| 1 | English | 3 |
| 2 | Second Language | 3 |
| 3 | Communication Skills (or) Professional Skills (sec I) | 3 |
| 4 | Theory Of Equations (or) Logic And Sets (or) Python I (or) Data Collection, Presentation, Interpretation (or) Mini Project (sec II) | 2 |
| 5 | Real Analysis | 5 |
| 6 | Statistical Methods And Estimation | 5 |
| 7 | Data Structures Using C++ | 5 |
| S no | SEM - IV | Credits |
|---|---|---|
| 1 | English | 3 |
| 2 | Second Language | 3 |
| 3 | Leadership And Management Skills (or) Universal Human Values (sec III) | 2 |
| 4 | Number Theory (or) Vector Calculus (or) Python II (or) Data Scaling Tecniques And Report Writing, Mini Project(sec IV) | 2 |
| 5 | Algebra | 5 |
| 6 | Statistical Inference | 5 |
| 7 | Machine Learning | 5 |
| S No | SEM - V | Credits |
|---|---|---|
| 1 | English | 3 |
| 2 | Second Language | 3 |
| 3 | GE (generic Elective) | 4 |
| 4 | Linear Algebra | 5 |
| 5 | Applied Statistics I (or) Analytical Statistics I | 5 |
| 6 | Natural Language Processing (or)No Sql Databases | 5 |
| S No | SEM - VI | Credits |
|---|---|---|
| 1 | English | 3 |
| 2 | Second Language | 3 |
| 3 | Major Project | 4 |
| 4 | Numerical Analysis (or) Integral Transforms (or) Analytical Solid Geometry | 5 |
| 5 | Applied Statistics II (or) Analytical Statistics II | 5 |
| 6 | Big Data (or) Deep Learning | 5 |
