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PY-DS: Python for Data Science

This Python for Data Science (PY-DS) course outline provides a complete roadmap for mastering data manipulation, cleaning, and visualization using industry-standard libraries. It typically covers programming fundamentals, NumPy, Pandas, and data visualization tools, culminating in a practical capstone project
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Registered employers can fully claim the course fee and allowanced through the HRD Corp portal.

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Course Description

This course equips you with the foundational skills to extract, clean, analyze, and visualize data using Python. You will transition from writing basic scripts to building full data analysis pipelines using industry-standard libraries like NumPy, Pandas, Matplotlib, and Seaborn. Through hands-on projects, you will learn how to turn raw, messy data into actionable business insights and predictive models.

Course Outline

Basic Syntax: Variables, data types (strings, integers, floats, booleans), and operators.Control Structures: if-else statements, for and while loops.Functions & OOP: Creating custom functions (with arguments/keywords), lambda functions, and basic class structures.

Core Structures: Lists, dictionaries, tuples, and sets.Comprehensions: Using list and dictionary comprehensions for efficient code.File I/O: Reading and writing .csv, .txt, and .json files

NumPy: Introduction to arrays, vectorization, and mathematical operations (mean, median, standard deviation).Pandas Series & DataFrames: Data loading, inspection, and indexing.Data Preparation: Handling missing values, filtering, grouping (groupby), merging, and reshaping messy datasets.

Matplotlib: Creating foundational charts like line graphs, scatter plots, and histograms.Seaborn: Advanced statistical graphics, correlation heatmaps, and pair plots

Scikit-Learn Basics: Building, training, and evaluating predictive models (e.g., Linear Regression, Classification).Exploratory Data Analysis (EDA) Pipeline: Applying the data science lifecycle from data cleaning to evaluation

Registration Details
Duration 7 Days
Individual Fee

RM 4,000.00

Exclusive of 8% SST

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