Python Training Fast Track III – for Data Science

This Python training course aims to efficiently equip learners with the fundamental and advanced skills required to use Python for data analysis and visualisation.

Module 1:  Introduction to Python for Data Science

•    Overview of Python in Data Science
•    Setting up the Python environment (Anaconda, Jupyter Notebook, VS Code)

Module 2:  Working with Data in Python

•    Introduction to NumPy for numerical computing

• Creating and manipulating arrays
• Array operations and broadcasting

•    Introduction to Pandas for data manipulation

• DataFrames and Series
• Reading and writing data (CSV, Excel, JSON, SQL)
• Data selection, filtering, and transformation

Module 3: Data Cleaning and Preprocessing

•    Handling missing data
•    Data imputation techniques
•    Detecting and removing duplicates
•    String operations and text cleaning

Module 4: Data Visualization

•    Introduction to Matplotlib

• Creating basic plots (line, bar, scatter)
• Customising plots (labels, colors, legends)

•    Introduction to Seaborn

• Statistical data visualisation (histograms, box plots, heatmaps)

•    Interactive visualisation with Plotly

Module 5: Exploratory Data Analysis (EDA)

•    Understanding distributions and summary statistics
•    Identifying patterns and trends in data
•    Correlation and covariance
•    Detecting and handling outliers
•    Using Pandas Profiling and Sweetviz for automated EDA

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