FUNDAMENTALS OF DATA SCIENCE

Course Description

This course focuses on learning data science through the interest to development and improvement of capability of solving rich problems from data point of view in a systematic and principled way by using high quality instructions and basic level data science techniques. Students will be introduced to what data science is, will discover the applicability of data science across fields, and will learn how data analysis can help them make data driven decisions. Students will gain familiarity with various open source tools and data science programs used by data scientists, like Jupyter Notebooks, RStudio, GitHub, and SQL. This course provides the students with the required structure and responsibilities in order to educate them as data scientists progressing a right way with high concluding capabilities.

FUNDAMENTALS OF DATA SCIENCE

Evaluation Tools (Active Term)

Course outcomes

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Course Syllabus

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Reference Books & Course Materials

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Learning Outcomes

1. L01 1. Students will be able to explain fundamental concepts of data science, including data types, workflows, and applications. 2. Students will be able to perform basic data preprocessing, including cleaning, transforming, and organizing datasets. 3. Students will be able to create and interpret basic data visualizations using charts and plots. 4. Students will be able to apply basic statistical concepts such as mean, variance, correlation, and probability distributions. 5. Students will be able to use data science methods to solve simple real-world problems. SOLO 1

Program Outcomes

1. P01 Be able to apply knowledge of programming
2. P02 Be able to design software systems of varying complexity
3. P03 Be able to identify, categorize, and develop solutions for computer orientated challenges.
4. P04 Be able to demonstrate autonomy and responsibility in managing computer programming projects
5. P05 Be able to follow the state of the arts concepts in computer technology
6. P06 Be able to design, implement, and evaluate a computational system to meet desired needs within realistic constraints.
7. P07 Be able to use appropriate techniques, skills, and tools necessary for computing practice.
8. P08 Be able to apply appropriate technologies and techniques for the collection and analysis of organizational and environmental data to facilitate evidence-based decision making
9. P09 Be able to apply effective communication skills consistent with the professional environment -
10. P10 Be able to apply effective collaboration skills in teamwork consistent with the professional environment -

Po-Lo Matrix