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Data Analytics with Python


Faculty of Electrical Engineering Universiti Teknologi MARA, Meng. in Electrical Engineering, Universiti Teknologi Malaysia (2012), BEng.(Hons) in Electrical Engineering (Telecommunication) – First Class, Universiti Teknologi Malaysia (2008)

What you will learn

Learn how to analyze data using Python. This course will take you from the basics of Python to exploring many different types of data. You will learn how to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more.


Anyone who wants to use Python programming language to do Data Analysis.


Python programming knowledge preferred.

Course objectives

The course will introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Series and Data Frame as the central data structures for data analysis, along with tutorials on how to use functions such as group by, merge, and pivot tables effectively. By the end of this course, participants will be able to take tabular data, clean it, manipulate it, and run basic inferential statistical analyses.

Investment Chart

Course outline

Module 1: Data Preparation

•    Data Analytics with Pandas
•    Pandas Data Frame and Series
•    Import and Export Data
•    Filter and Slice Data
•    Clean Data

Module 3: Data Visualization

•    Creating data sets
•    Creating data frames

Module 2: Data Transformation

•    Join Data
•    Transform Data
•    Aggregate Data

Module 4: Data Manipulation, Simple Statistics and Data Plotting Using Pandas

•    Finding Maximum & Minimums
•    Calculating and identifying outliers
•    Indexing and Selecting Data
•    Reshaping and Pivot Tables
•    Time Series / Date functionality
•    Categorical Data
•    Simple Statistical Analysis

Module 5: Data Analysis

•    Statistical Data Analysis
•    Time Series Analysis

Module 6: Machines Learning

•    Introduction to Machine Learning
•    Supervised Learning: Regression
•    Supervised Learning: Classification

Analyzing Data


This program will be presented via interactive lecture and practical hands-on activities.
•    2 Days with 7.5 hours per day
•    Time 09:00 - 17:30
•    HRDF SBL Claimable
•    Certificate of Attendance available

HRDF testimonial video

All our courses are HRDCorp-certified

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