Summary Foundations of Data Science - CS3352 (CS3352)
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Course
CS3352 (CS3352)
Institution
Anna University
Book
Foundations of Data Science
he text outlines foundational data science topics, including data manipulation with Pandas and visualization with Matplotlib, SQL for database management, machine learning algorithms, and advanced topics in big data and business analytics.
Foundations of Data Science
TOPICS :-
1) Introduction to Data Science: Exploring Real-World Problems
2) Mathematical Foundations: Statistics, Probability, and Calculus
3) Data Manipulation and Visualization: Pandas and Matplotlib
4) Machine Learning Algorithms
5) SQL and Database Management: Data Storage and Handling
6) Projects and Portfolio Building: Kaggle and Github
7) Advanced Topics: Specialization in Big Data, Algorithms, or Business
1)Introduction to Data Science: Exploring Real-World Problems (Focusing on Data
Manipulation and Visualization)
Data Manipulation and Visualization
Pandas
Introduction to Pandas: A powerful data manipulation library for Python.
Key features:
DataFrames: 2-dimensional labeled data structure with columns of potentially
different types.
Series: One-dimensional labeled array capable of holding any data type.
Basic Operations:
Reading and writing data.
Filtering and slicing data.
Merging, joining, and concatenating data.
Grouping and summarizing data.
Matplotlib
Introduction to Matplotlib: A plotting library for Python.
Key features:
Static, animated, and interactive plots.
Various plot types: line, scatter, bar, histogram, etc.
Distributed computing: Apache Hadoop, Spark, etc.
Algorithms:
Machine learning algorithms for regression, classification, clustering, etc.
Optimization techniques for large-scale data.
Business:
Quantitative analysis: statistical methods, risk management, etc.
Decision-making: data-driven insights, resourcing, etc.
SQL and Database Management
Data Storage and Handling
Introduction to SQL (Structured Query Language): A language for interacting with
relational databases.
Key features:
Defining data structures.
Inserting, querying, updating, and deleting data.
Basic Operations:
Creating and managing databases and tables.
Writing, reading, and modifying data using SELECT, INSERT, UPDATE, DELETE
statements.
Projects and Portfolio Building
Kaggle: A platform for predictive modelling and analytics competitions.
GitHub: A platform for hosting and sharing code, documentation, and projects.
Introduction to Data Science: Exploring Real-World Problems (Cont.)
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