STAT575 Computational Tools for Data Science
| Course Code: | 2460575 |
| METU Credit (Theoretical-Laboratory hours/week): | 3 (3.00 - 0.00) |
| ECTS Credit: | 8.0 |
| Department: | Statistics |
| Language of Instruction: | English |
| Level of Study: | Graduate |
| Course Coordinator: | Prof.Dr. ÖZLEM İLK DAĞ |
| Offered Semester: | Fall and Spring Semesters. |
Course Objectives
The objective of this course is to have students gain the experience in using R and Python for data science, comparing several programming languages, and learning distributed systems and streaming systems.
Course Content
Programming with R and Python for statistics and data science computing. Computing using statistical software. Relational, distributed, parallel and object databases. Structured query language (SQL). Big data storage systems. Data warehouses. Online analytic processing (OLAP). Big data handling tools and techniques. Web data management. Cloud computing.
Course Learning Outcomes
By the end of the course the students will be able to:
- Use R for data science
- Use Python for data science
- Visualize data with R and Python
- Acquire the ability to use the techniques and tools necessary for data science
- Compare several programming languages for data science
- Learn the basics of large-scale data storage and cloud computing
- Handle with distributed computing systems
- Learn real-time streaming systems
Program Outcomes Matrix
| Level of Contribution | |||||
| # | Program Outcomes | 0 | 1 | 2 | 3 |
| 1 | Ability for converting theoretical, methodological, and computational statistical knowledge into analytical solutions in researches requiring statistical analyses. | ✔ | |||
| 2 | Ability for specifiying problems in real life situations bearing uncertainty, forming hypotheses, modeling, application, and interpreting the results. | ✔ | |||
| 3 | Ability for using current technology, computer softwares for statistical applications, computer programming for specific problems when necessary, writing computer codes for speeding up statistical calculations, organizing and cleaning databases, and preparing them for statistical analyses, and data mining. | ✔ | |||
| 4 | Ability for taking part in intra/inter disciplinary team work, efficient use of time, taking responsibility as a team leader, and entrepreneurship. | ✔ | |||
| 5 | Ability for taking responsibility in solitary work and producing creative solutions. | ✔ | |||
| 6 | Ability for keeping up-to-date with current advancements in statistical sciences, doing research, being open-minded, and adopting critical thinking. | ✔ | |||
| 7 | Ability for effective communication both in Turkish and English in specification of statistical problems, analyes, and interpretation of findings. | ✔ | |||
| 8 | Ability for using the knowledge in the field of expertise for the welfare of the society. | ✔ | |||
| 9 | Ability for suggesting the researchers in a comprehensible way the appropriate statistical methods for problems in fields that use statistics such as economics, finance, industrial engineering, genetics, and medicine and apply if needed. | ✔ | |||
| 10 | Ability for catalyzing discussions and presentations, public speaking, making presentations, communicating topics of expertise to the audiance in a comprehensible way. | ✔ | |||
0: No Contribution 1: Little Contribution 2: Partial Contribution 3: Full Contribution