Data Analytics with Python

This prerecorded 12 Hours shortcourse is about Data Analytics by using Python.

Python data analysis is a crucial ability for data analysts and data scientists. You will learn the fundamentals of data analysis using Python in this course before developing and analysing data models.

You will learn how to do exploratory data analysis (EDA), clean and manage data, importing data from various sources, and produce useful data visualizations. The next step is to create linear, multiple, polynomial regression models & pipelines and learn how to assess them in order to forecast future trends from data.

You will study and practise utilising practical laboratories and projects in addition to video lectures. To import, modify, analyse, and display fascination datasets, you’ll use a variety of open-source Python modules, such as Pandas and Numpy alongside other available modules.


Course details:

  1. Fundamental Python Programming for Data Analytics
  2. Exploratory Data Analysis (Cleaning, Testing, Analysis)
    & Reading, Visualizing, and Analyzing data from various data sources
    & Using Data Analytics library (Numpy, Pandas, Matplotlib, etc)
  3. Predictive Analytics and Machine Learning – Regression
  4. Predictive Analytics and Machine Learning – Clustering
  5. Predictive Analytics and Machine Learning – Classification


The objectives of this course are to :

  1. To gain a deeper understanding and knowledge in Python.
  2. Understand techniques used for handling data such as cleaning and analyzing.
  3. Able to describe data and visualize them into meaningful information.

Instructor :

  1. Ts. Dr. Mohd Zamri Osman -Senior Lecturer at UNIVERSITI TEKNOLOGI MALAYSIA (UTM) Certified Data Science Analyst | Certified Data Engineering | Applied Machine Learning
  1. Dr. Muhammad Akmal Remli –Director at Institute for Artificial Intelligence and Big Data (AIBIG) and Senior Lecturer at Faculty of Data Science and Computing, UMK


Target Group :

  1. Students & Researcher interested in learning Python Programming
  2. Anyone interested in learning Python
  3. Industry or Organization interested in Data Analytics


Notes & Codes

Basic Phython

Introduction to Python
37 Min
Data Types & Operator
15 min
Variables, Expressions & Statements
18 min
40 min
Conditional Branching & Looping
30 min
Build in & User Defined Function
11 min
Data Structures With List, Tuple & Dictionaries
1 Hour 35 Min

Exploratory Data Analysis

Importing Datasets, Data Wrangling, Exploratory Data Analysis
1 hr 25 min
Data Visualization
35 Min

Machine Learning (Regression Clustering Classification

Introduction to Machine Learning
1 Hour 20 Min
1 Hour 25 Min
2 Hours
2 Hours

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Data Analytics with Python