Foundations for Data Science
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Foundations for Data Science Syllabus — Unit-wise Content
The official GTU curriculum for Foundations for Data Science (subject code 1719502) as prescribed for AIAD · Semester 1 divides the course into 5 units, covering 41 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.
Download the official syllabus PDF (1719502)Unit 1 Fundamentals of Data Science
- Introduction to data science
- Data analytics life cycle
- Type of data analysis
- Types of jobs in data analytics
- Data science tools
- Fundamental areas of study in data science
- Role of SQL in data science
- Pros and cons of data science
Unit 2 Data Preprocessing, Plotting and Visualization
- Data types and forms
- Possible data error types
- Various data preprocessing operations
- Introduction to data visualization
- Visual encoding
- Data visualization libraries
- Basic data visualization tools
Unit 3 Statistical Data Analysis and Machine Learning 10 25%
- BRANCH: COMPUTER ENGINEERING (ARTIFICIAL INTELLIGECNE AND DATA SCIENCE) Page 2 Role of statistics in data science
- Descriptive statistics
- Inferential statistics
- Overview of machine learning
- Supervised machine learning
- Regression methods
- Classification methods
- Unsupervised machine learning
- Clustering methods
- Association analysis
Unit 4 Time-series Analysis
- Overview of time-series analysis
- Components of time-series
- Time-series forecasting models
Unit 5 Ethics and Data Science
- The Five Cs: Consent
- Consistency and Trust
- Control and Transparency
- Implementing Five Cs, Data’s Day of Reckoning
- Ethics and Security Training
- Developing Guiding Principles
- Building Ethics into Data-drive Culture
- Regulation 5 Recent Trends in the Domain of Data Science 6 15% Textbook: 1
- Data Science Fundamentals and Practical Approaches by Gypsi Nandi and Rupam Kumar Sharma First Edition
- BPB Publications India. 2
- Ethics and Data Science by Mike Loukides
- Hilary Mason
- & D J Patil First Edition
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