Data Science
Python for Data Science
Learn data science fundamentals using Python. Master NumPy, Pandas, and Matplotlib for data analysis and visualization skills.
About this Course
Overview:
This course equips participants with fundamental skills for data science careers using Python. Learners master data manipulation and analysis through NumPy, Pandas, and Matplotlib libraries. The program culminates in performing basic data analysis tasks and creating effective data visualizations, followed by a 4-week capstone project.
Course Outline
- Introduction to Data Science and Python
- Setting up Python environment (Anaconda, Jupyter Notebook)
- Python basics: variables, data types, operators, control flow
- Introduction to Lists and Tuples
- Using Sets
- Using Dictionaries
- Introduction to NumPy arrays
- Array creation and manipulation
- Array indexing and slicing
- Array operations and functions
- Introduction to Pandas DataFrame and Series
- Reading and writing data using Pandas
- Data manipulation with Pandas
- Data cleaning and preprocessing
- Introduction to Matplotlib
- Basic plots: line plot, scatter plot, bar plot
- Customizing plots: labels, titles, colors
- Multiple plots and subplots
- Understanding the dataset
- Descriptive statistics
- Data summarization and aggregation
- Data visualization for EDA
- Handling missing values
- Data transformation: normalization, scaling
- Data merging and joining
- Data reshaping
- Basics of machine learning
- Supervised vs. unsupervised learning
- Introduction to scikit-learn library
- Real-world dataset application
- Data analysis and visualization
- Project presentation and evaluation
