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Python for Data Science

CDC-PDS

Master Python for data analysis, visualization, and machine learning. This course covers the full data science pipeline using Pandas, NumPy, Matplotlib, Scikit-learn, and more.

Fees:

RM 6,500.00

Course duration:

5 days

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Move beyond spreadsheets. Use Python to analyze, visualize, and predict with confidence.

From data wrangling to machine learning — get hands-on with real projects that showcase your skills.

Build your portfolio and become the data-driven decision-maker every organization needs.

Course Overview

In the age of data, those who can extract insights hold the competitive edge. This 5-day instructor-led course equips learners with the Python programming skills needed to solve real data science challenges.


You’ll begin with foundational Python syntax, then move on to powerful tools like Pandas for data manipulation, Matplotlib and Seaborn for visualization, and Scikit-learn for machine learning. You’ll also work on a real-world recommendation system project and apply ML models to real datasets.


Ideal for aspiring data scientists and analysts, this course gives you both theory and practical exposure to the most in-demand Python libraries used in the field today.

Learning Objectives

  • Python fundamentals for data science

  • DataFrames and cleaning using Pandas

  • Numerical computing with NumPy

  • Statistical and advanced data visualization

  • Recommendation engine design

  • Supervised and unsupervised ML with Scikit-learn

  • Model evaluation and hyperparameter tuning

  • Basics of NLP, deep learning, and time series

  • End-to-end project execution with real-world data

Who Should Attend

  • Beginners in data science and analytics

  • Analysts and Excel users transitioning to code

  • Python developers exploring data applications

  • Business intelligence professionals seeking deeper analysis tools

  • Students or graduates building a data science portfolio

Prerequisites

  • Basic understanding of programming concepts such as variables, functions, and loops.

  • Familiarity with algebra and statistics is recommended.

Course Modules

Module 1: Python for Data Science

  • Set up your Python environment and learn the essentials: variables, data types, control flow, and file handling.


Module 2: Data Manipulation with Pandas

  • Work with Series, DataFrames, and clean messy datasets. Learn grouping, merging, and advanced operations.


Module 3: Analysis and Visualization

  • Use NumPy for computation and create insightful visuals with Matplotlib and Seaborn.


Module 4: Recommendation Engine

  • Design and build a movie recommendation system using collaborative filtering and correlation techniques.

Modules 5–6: Intro to Machine Learning

  • Understand ML types, preprocessing, feature engineering, and data splitting for model development.


Module 7: ML with Scikit-learn

  • Build regression, classification, clustering models, evaluate them, and tune hyperparameters for optimal performance.


Module 8: Advanced Topics & Project

  • Explore NLP, time series, and deep learning fundamentals. Apply everything through a capstone project on real data.

Professional Outcomes

This course supports roles such as Data Analyst, Python Developer for Data, Junior Data Scientist, or Business Analyst — empowering learners to build dashboards, models, and data products independently.

Certification Details

No specific exam for this course

Frequently Asked Questions

Is this course suitable for absolute beginners?

Yes. This course starts from the basics and gradually moves to advanced data science concepts.

Do I need to know machine learning beforehand?

No. The course covers the fundamentals of machine learning and explains them in a beginner-friendly way.

Are real datasets used in the training?

Yes. You will work with real-world datasets in exercises and projects.

Will I build a recommendation engine?

Yes. One module is dedicated to designing and implementing a recommender system.

Does this course include a capstone project?

Yes. The final module includes an applied project using the techniques taught throughout the course.

Are libraries like Pandas, Matplotlib, and Scikit-learn included?

Yes. The course focuses heavily on the most popular and powerful Python data libraries.

Is this course certification-based?

No. This is a skills-based course focused on project execution and hands-on proficiency.

Is this course HRDC claimable?

Yes. It is claimable under HRDC for eligible Malaysian employers.

Can this course be customized for our internal team?

Yes. GemRain offers both in-house and virtual delivery for organizations.

Will I get a certificate of completion?

Yes. You will receive an official GemRain certificate upon completing the course.


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