Python for Data Science: Certification by iTrain Malaysia

Python for Data Science

Duration: 4 Days (Beginner to Intermediate) + 3 (Advanced) |
HRDF Claimable!

Python for Data Science Course Overview

Python is a general-purpose programming language that is becoming more and more popular for analysing datasets and conducting data science processes. Companies worldwide are using Python to harvest insights from their data and gain a competitive edge. Unlike any other Python tutorial, this class will teach on various environments for project development to let you choose your best one. All the steps to construct a data science project will be taught starting from data importing, data cleaning, data analysing and ending with data visualization to get new insights. In summary, getting certified in Python for Data Science will give you a complete understanding on Python from the ground up.

Learning Outcomes

Upon completion of this course, you will be able to:

  • Understand all of the basics of Python
  • Develop and write code easily in Python
  • Deal with different sources of data
  • Analyse and visualize the data in order to get new insights from the data

Course Outline


Beginner to Intermediate (4 Days)

  • What is Algorithm?
  • What is Programming?
  • The Natural Language of The Computer
  • Machine Language
  • Programming Language Levels
  • Translators

  • Identifiers, Lists, and Tuples
  • Dictionaries, Sets and Strings
  • Operators, Control Structures and Loops

  • Installing and Running Jupyter
  • User Interface
  • Checkpoints

  • Function
  • Lambda and Map Function
  • Globals and Locals

  • List Comprehension
  • Generator Expressions
  • Exceptions Handling

  • Modules
  • Documentation
  • Packages and Namespaces

  • Create, Read, Update, Delete (CRUD) a File

  • What is JSON and Why It is Important
  • Module, Serialization, Deserialization

  • What is Web Scrapping
  • HTML Tags
  • BeautifulSoup Module
  • Webpage Scrapping Phase

  • What is NumPy?
  • Ndarray Object, Data Types
  • Array Attributes, Array Creation and Routines
  • Indexing and Slicing
  • Array Manipulation
  • Mathematical Functions

  • Series, Dataframe
  • Data Importing, Pre-processing, and Grouping

  • Line, Bar, Pie Graph
  • Histogram, Scatter Plot
  • Graph Attributes, Text Annotation

  • ML Algorithm Types
  • Main Steps in ML Projects
  • Introduction to Scikit Learn Module

Advanced (3 Days)

  • What is ML and The Steps
  • Introduction to SK Learn

  • What is Dataset, Iris Dataset
  • Handwritten Digits Dataset
  • Dataset Distribution

  • Key Clustering Algorithms
    • K-Means
    • Mean Shift
  • Principal Component Analysis
  • Dimensionality Reduction

  • Key Classifiers Algorithms
    • K-Nearest Neighbors (KNN)
    • Support Vector Machine (SVM)
    • Decision Tree (DT)
  • Performance Metrics and Errors
  • Regression

  • Multi-Layer Perceptron Classifier, Hidden Layers
  • Activation Function, Solver

  • Basic Text Analysis with Python
  • Introduction to NLTK

  • Tokenize Words and Sentences
  • Stop Words, Regular Expressions
  • Stemming, POS Tagging

  • Popular NLTK Corpus
  • Build Your Own

  • NLTK and Scikit Learn

  • Word2Vec Algorithm
  • CBOW and Skip-gram Models

  • Introduction to Networkx Module
  • Network Connectivity
  • Influence Measures and Network Centralization

“A good course to dive into data science – covers both theory and practical.”

Dr. Jaspaljeet, Lecturer, UNITEN

“This course is the perfect foundation for anyone interested in Data Science, as it gives you a general understanding of the subject matter but excited enough to want to dive in deep.”

Yassif Nagim Mustafa, Data Engineer, Nusatara Software Sdn Bhd

“Interesting class to attend to learn something beyond the work, and yet applicable to work.”

Cheok Swin Voon, Advisory IT Specialist, IBM Malaysia

“This is a very good course to attend. thumbs up to the school and the trainer. Highly recommended! Thanks iTrain!”

Syed Shahiful Adli, Associate, Customer Journey Design, ASTRO

“I participated in this course to understand further about data science, and how it can be applied to our company’s decision making. The training not only covered those topics, but gave a thorough guide on exploring future careers working with data.”

Chong Nin, Project Executive, ECMI ITE Asia Sdn Bhd



Students will be given a Certificate of Attendance after successfully completing the course.

You bet it is! Our Certification Body for this course is iTrain Asia Pte Ltd, the region’s top Certifications Tech Provider headquartered in Singapore, with branch offices in Malaysia and Indonesia.

Upon completion of this course, you will be able to:

● Explain the workflow of data science and applying data science concepts with Python
● Analyzing and solving data science datasets with Python

This is a 4-day course for Beginner to Intermediate and 3-day course for Advanced at an instructor-led training centre.

Computers are provided for iTrain students. However participants can also use their own computers as long as it’s installed with the necessary applications.

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