data science-01.jpg

Conquer Data Science
With Python 

Course Price

Discounted Price

RM 3,000

RM 1,000

(Limited Time Offer)

Duration: 10 days/40 hours

Course Preview

Register for Free Python Beginner Course



This course is a 40 Hours curriculum intended for those who have a basic knowledge of python programming. In this course, we will learn the basics of conducting data science, how to perform data analysis in python and then create some beautiful visualizations using Python. This data science course also summarizes many concepts, techniques, and algorithms in machine learning, beginning with topics such as linear regression and ending up with three projects.



- 40 hours training
- 4-5 industry-related projects
- Experienced instructor
- Basic to intermediate level 



- How to wrangle data, or Data wrangling
- Learning to explore data or Data exploration
- Visualising data
- Learning how to scrap data from various sources or datasets
- Fundamentals of Python programming 
- Data Science libraries 



- Software Professionals
- IT Professionals
- Analytics professionals
- Data Scientist
- Data Analyst
- Fresh Graduates
- Anyone with a genuine interest in Data Science



- Our aim is to provide everyone vital hands-on experience so that you are well-prepared for job interviews alongside an exhibition at their positions
- Learn from pioneers in Data Science, both in research and industry.
- Learn the tricks of the trade from seasoned Python Developer
- Work on hands-on projects that develop your ability to solve real-world problems.

- Practice your skills on our hands-on projects that simulate real-world problems

- How to wrangle data

- Learning to explore data

- Visualizing data

- Learning how data is scrapped from various datasets or sources

- Fundamentals of Python programming



- 100 % Hands-on Training 
- 40 Hours Instructor-led Training 
- 3 Projects
- Certifications, videos and resources 
- Weekly assignments and assessments 
- Industry-relevant content



- Hands-on Exposure to Data Science 
- Work on real-world projects in Data Science 
- Create your own applications for data retrieval, processing, and visualization



- Comprehensive Blended Learning program

- flexible access to online classes

- instructions carried out through industry experienced trainers

- Interactive Quizzes

- 15+ in-demand technologies and skills

- Get hands-on experience with four industry-related projects

- 24x7 learner assistance and support



The inquiry process comprises three simple steps.

STEP 1 Submit Inquiry- Tell us a bit about yourself and the questions you want to enquire

STEP 2 Reviewing–Your questions will be processed and answered within a day or two 

STEP 3 Response–Answers will typically be sent through email. However, you may tell us the option you prefer us to contact you in



- Physical Classroom Training (Malaysia)

- On-site Company Training (Malaysia)

- Online Training via Microsoft Team (Malaysia and International)



The admission fee for this Data Science with Python certification program is RM 1,000.

Duration: 10 days/40 hours



- 40 hours of Python Tutorial Beginner Kit contains a pre-recorded video on the basics of python programming
- 40 Hours of Hands-On Practice
- 40 Hours of Assignments
- Industry Relevant Projects
- Certifications, Videos and Resources
- Weekly assignments and assessments



Module 01

Data Science Overview Introduction to Data Science Different Sectors Using Data Science Purpose and Components of Python
Module 02

Data Analytics Overview
Data Analytics Process Knowledge Check
Exploratory Data Analysis(EDA) EDA-Quantitative Technique EDA -Graphical Technique
Data Analytics Conclusion or Predictions Data Analytic s Communication
Data Types for Plotting Data Types and Plotting


Module 03

Statistical Analysis and Business Application
Introduction to Statistics
Statistical and Non- statistical Analysiss Major Categories of Statistics Statistical Analysis Considerations Data Distribution
Knowledge Check Histogram Testing
Correlation and Inferential Statistics


Module 04

Python Environment Setup and Essentials
Installation of Anaconda Python Distribution (contd.) Data Types with Python
Basic Operators and Functions
Module 05

Mathematical Computing with Python (NumPy)
Introduction to NumPy Activity-Sequence it Right
Demo 01- Creating and Printing and narray
Knowledge Check Class and Attributes of ndarray Basic Operations
Activity-Slice It Copy and Views
Mathematical Functions of NumPy Mathematical Functions of NumPy


Module 06

Scientific computing with Python (SciPy)
Introduction to SciPy
SciPy Sub Package - Integration and Optimization Knowledge Check
SciPy sub package
Demo - Calculate Eigenvalues and Eigenvector Knowledge Check
SciPy Sub Package - Statistics, Weave and IO Solving Linear Algebra problem using SciPy Assignment 01 Demo
Perform CDF and PDF using Scipy

Module 07

Data Manipulation wit h Pandas
Introduction to Pandas

Knowledge Check Understanding Data Frame View and Select Data Demo Missing Values
Data Operations Knowledge Check
File Read and Write Support Knowledge Check- Sequence it Right Pandas Sql Operation
Analyze the Federal Aviation Authority Dataset using Pandas
Assignment 01 Demo
Analyze New York city fire department Dataset


Module 08

Machine Learning with Scikit–Learn
Machine Learning Approach Steps One and Two
Steps Three and Four How it Works
Steps Five and Six
Supervise d Learning Model Considerations Scikit Learn
Supervised Learning Models- Linear Regression
Supervised Learning Models- Logistic Regression Unsupervised Learning Models
Model Persistence and Evaluation Knowledge Check
Analyzing Ad Budgets for different media channels
Model Persistence and Evaluation Knowledge Check

Building a model to predict Diabetes


Module 09

 Natural Language Processing with Scikit Learn
NLP Overview NLP Applications Knowledge Check
NLP Libraries- Scikit Extraction Considerations
Scikit Learn- Model Training and Grid Search
Analyzing Spam Collection Data Demo
Sentiment Analysis using NLP


Module 10 

Data Visualization in Python using Matplotlib
Introduction to Data Visualization Knowledge Check
Line Properties
(x,y) Plot and Subplots Knowledge Check Types of Plots
Draw a pair plot using the seaborne library

Assignment 01 Demo
Analysing Cause of Death


Module 11

Web Scraping with Beautiful Soup
Web Scraping and Parsing Knowledge Check
Understanding and Searching the Tree

Demo3 Navigating a Tree Knowledge Check Modifying the Tree
Parsing and Printing the Document Web Scraping of any Website


Module 12

Python integration with Hadoop Map Reduce and Spark
Why Big Data Solutions are Provided for Python Hadoop Core Components
Python Integration with HDFS using Hadoop Streaming
Demo 01 - Using Hadoop Streaming for Calculating Word Count Knowledge Check
Python Integration with Spark using PySpark
Demo 02 - Using PySpark to Determine Word Count Knowledge Check
Determine the word count
Assignment 01 Demo
Display all the airports based in New York using PySpark

Objectives / What You Will Learn
Explore Python fundamentals, including basic syntax, variables, and types Create and manipulate regular Python lists
Use functions and import packages
Build NumPy arrays, and perform interesting calculations Create and customize plot son real data
Supercharge with control flow and get to know the Pandas Data Frame
Use Python to read And write files Illustrate Supervised Learning Algorithms
Identify and recognize machine learning algorithms around us

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