Python for Data Science

Learn about several Python libraries for storing, manipulating, and gaining insight from data

  • Get up to 90% SkillsFuture Singapore (SSG) subsidy and also utilize your SkillsFuture Credit!
  • Master Python to manipulate and gain insights from data
  • 32 hours of live and interactive, instructor-led training
  • Gain from real-time code analysis with feedback from industry experts


KnowledgeHut’s skill development Python for Data Science workshop is focused on helping professionals gain industry-relevant data science expertise. Learners can avail of the instructor-led training which is of 32 hours duration. 

The program will cover all the essential Python for Data Science skills that are the most sought-after across industries. Currently, the expertise available in this field is highly fragmented and aspirants who want to become data scientists need to skill up to meet industry demands. This program addresses the main challenges faced by tech-focused organizations — equipping the workforce with the right development skills and ensuring that best practices are followed.  

This hands-on interactive workshop with a path-breaking curriculum, and guided mentorship is your ticket to launch a career as a Data Analyst. Laying emphasis on reason-based learning, the curriculum is split into easily comprehensible modules that cover the latest advancements in data science and Python. Starting with Python syntaxes and data types, you will move on to Python objects and the various operations associated with them. You will then dive deep into coding best practices, Numpy, Pandas, and visualization techniques. Finally, you will cover exploratory data analysis and the advanced techniques that are used to draw data insights. Along the way, you will gain hands-on expertise on various topics.

You will learn from expert data scientists who will help you bridge the skill gap and get ready for the industry by mastering Python.   

What You Will Learn


Anybody who is a Data Science aspirant with coding or non-coding background

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The Python for Data Science program is approved under the SkillsFuture Singapore (SSG) initiative of the Singapore Government and is qualified for subsidies under different schemes, subject to meeting the required criteria. Individuals and corporates can benefit from subsidies under this scheme as follows:

INDIVIDUALS: Up to 90% subsidy for Singapore Citizens and Permanent Residents meeting eligibility.
CORPORATES: Singapore-based Small and Medium Enterprises (SMEs) may submit claims for SSG-supported programmes. Refer FAQs for more details on how corporates can avail SSG subsidies.  

Individuals and Corporates
Amount Payable after SSG Subsidy (Until December 2021)
Amount Payable after SSG Subsidy (January 2022 Onwards)
Singapore Citizens and Permanent Residents  
Up to 50% of course fee with a maximum limit of $15 per hour
Up to 50% of course fee
Up to 80% of course fee with a maximum limit of $17 per hour
Singapore Citizens of 40 years or above  
Up to 90% of course fee with a maximum limit of $50 per hour
Up to 70% of course fee
Up to 90% of course fee with a maximum limit of $25 per hour
Singapore-Based Small and Medium Enterprises (SMEs)  
Up to 90% of course fee with a maximum limit of $50 per hour
Up to 90% of course fee with a maximum limit of $25 per hour


  1. PMET stands for Professionals, Managers, Executives and Technicians 
  2. All Singaporeans aged 25 and above can use their SkillsFuture Credit to pay for a wide range of approved skills-related courses. For more details, visit

*Terms and conditions apply. For more information on the SSG subsidies and eligibility, please refer our FAQs. For more details, please visit


The Singapore Government encourages Singaporeans to take timely action to upskill, reskill, and get better equipped to seize new career opportunities through the SkillsFuture Singapore (SSG) initiative. In addition to the SSG subsidy, every Singaporean aged 25 years and above can take advantage of the SkillsFuture Credit (SFC) to acquire the latest skills to prepare for future-ready job roles.

Not sure how to get started with applying for the SSG subsidy and making your SFC claims? Just follow these simple steps:

Step 1: Get enrolled
- Enrol into our SSG-approved Python for Data Science Course. 

Step 2: Apply for the SSG subsidy
- Once you enrol into the course, your KnowledgeHut Course Counsellor will attend to your interest and help you verify your SSG subsidy eligibility.
- Guiding you through the enrolment process under the SSG subsidy scheme, the Course Counsellor will advise you on your maximum subsidy eligibility.

Step 3: Apply for the SFC claim
- Check out KnowledgeHut’s upcoming schedules and select a workshop on a date convenient to you. An invoice will be issued to you with the fee breakdown.
- Follow this step-by-step process in the MySkillsFuture portal:
a. Login to the MySkillsFuture portal, select the course you’re enrolling into and enter course date and schedule
b. Enter the course fee payable by you (including GST) and enter the amount of credit to claim
c. Upload your invoice and click ‘Submit’

Step 4: Enjoy your course
- Get the SSG subsidy, utilize your SFC credits and skill up!

In addition to the SSG subsidy, all Singaporeans aged 25 and above can use their SkillsFuture Credit to pay for the Python for Data Science course. For more details on SkillsFuture Credit and the various approved skills-related courses, visit

Need help with checking your funding eligibility?

KnowledgeHut Experience

Instructor-led Online Classroom

Interact with instructors in real-time— listen, learn, question and apply. Our instructors are industry experts and deliver hands-on learning.

Curriculum Designed by Experts

Our courseware is always current and updated with the latest tech advancements.Stay globally relevant and empower yourself with the training.

Learn through Doing

Learn theory backed by practical case studies, exercises, and coding practice. Get skills and knowledge that can be effectively applied.

Mentored by Industry Leaders

Our experienced support team has experts with industry experience. They will guide and assist you whenever you require help.

Advance from the Basics

Learn concepts from scratch, and advance your learning through step-by-step guidance on tools and techniques.

Code Reviews by Professionals

Get reviews and insightful feedback from professional developers. Learn the industry best practices from the experts.

Who should Attend?

  • Those interested in data science who want to learn essential skills
  • Those new to Python and looking for a more robust, structured learning program
  • Software or Data Engineers interested in learning Python for Data Science


Learning Objectives

After completing this module, you will learn about Database development history, different types of data models and the key components of database and table.

Topics covered

  • Brief history of database
  • Commercial and open-source SQL products
  • Data models
  • Introduction to SQL

Learning Objectives

Students will be able to apply DDL operations like create, drop, truncate, alter and rename on a table.

Topics covered

  • Create Command
  • Drop Command
  • Truncate Command
  • Alter Command
  • Rename Command

Learning Objectives

Student will be able to apply DML operations like insert, update and delete records from/to a table.

Topics covered

  • Insert Command
  • Update Command
  • Delete Command

Learning Objectives

After completion of this module students will be able to fetch information from the tables using the select query, filter records from the table using While clause and sort records.

Topics covered

  • Select Query
  • Filtering Records
  • Where Clause Predicates
  • Sorting Records

Learning Objective:

After completion of this module students will be able to perform aggregate operations table columns, fetch outcome using grouped queries (GROUP BY), and summarize information using aggregate function with the group by clause.

Topics covered

  • count() Function
  • sum() Function
  • avg() Function
  • min() Function
  • max() Function
  • Distinct Keyword
  • Group By Clause
  • Summarizing Values

Learning objective:

This module will help students to use join clauses to gather information in a single table from multiple tables.

Topics covered

  • Inner Join
  • Left Join
  • Right Join
  • Full Outer Join
  • Self Join

Learning Objectives

Learn the basics of Python programming. This module will hand-hold a non-programmer to the programming world. You will learn writing basic Python syntaxes and understand basic Python data types. Learn writing logical conditions and performing data type conversion.

Topics covered

  • Jupyter Environment
  • Pseudocode
  • Using Print ()
  • Wrong usage of print()
  • Variables
  • Creating a variable
  • Reassign a variable
  • Multiple variable assignment
  • Data Types
  • Finding data types of variables
  • Data type conversion (Implicit)
  • Data type conversion (Explicit)
  • Arithmetic Operations
  • String Operations
  • Boolean Operations
  • String handling
  • Concatenation
  • if-else, loops
Learning Objectives
This module will introduce Python objects that are required in the field of data science. Understand various Python objects like Lists, Tuple, Dictionary & Sets and perform various operations on Python Objects. Also learn various functions associated with each of the Python objects.
Topics covered
  • What is Tuple?
  • Creating tuple
  • Tuple operations
  • Tuple: In-built function
  • What is a list?
  • Creating a list
  • List operations
  • List: In-built functions
  • List Joins
  • What is a set?
  • Creating a set
  • Set operations
  • Set: In-built functions
  • What is a dictionary?
  • Dictionary operations
  • Dictionary in-built functions
  • Conditional statements: if else
  • Conditional statements: nested if

Learning Objectives

This module introduces Numpy array for numerical computation. Learn what is a Numpy array and create Numpy arrays. Learn how to describe a Numpy array in terms of dimensions & size, and clearly differentiate between a Numpy array & a Python List.

Topics covered

  • What is python numpy
  • Functions to create array
  • Numpy operations - dtypes, size, shape, reshape, itemsize
  • Indexing array
  • Slicing array
  • Arithmetic operations on array
  • Arithmetic functions on array - sum(), min()
  • Concatenation of Arrays
Learning Objectives
This module introduces Pandas objects like Series & Dataframes. Learn what is a series object and perform various operations on a series object. Also learn what is a dataframe and how to perform various operations on a dataframe.
Topics covered
  • Python pandas
  • Data structures  
  • What is series?
  • Creating a series
  • Manipulating series
  • Usage if .loc and .iloc
  • What is a dataframe?
  • Creating a dataframe
Learning Objectives
This module takes you to the next level of operations on dataframes. Concatenate multiple dataframes vertically & horizontally, understand various kind of joins like inner join, outer join, left join & right join and learn the differences between concat, merge.
Topics covered
  • Manipulating dataframes
  • Indexing a dataframe
  • Read data from various sources
  • Concatenate the dataframes
  • Merge using inner join
  • Merge using outer join
  • Merge using right join
  • Merge using left join
  • Reshape using melt() function
  • Check for duplicates
Learning Objectives
This module takes you to the world of visualization that is necessary for analyzing data from data science perspective. Learn various kinds of plots, understand which plot to be used for specific analysis and learn using 2 key libraries - Matplotlib & Seaborn.
Topics covered
  • Plots using Matplotlib
  • Line plot
  • Scatter plot
  • Bar plot
  • Pie plot
  • Histogram
  • Box plot
  • Plots using Seaborn
  • Strip plot
  • Pair plot
  • Distribution plot
  • Count plot
  • Heatmap

Learning Objectives

This module introduces the fundamentals of data exploration with deeper insights. Learn the various techniques to analyse your data from various angles and summarize important Statistics. Also learn the advanced techniques to churn deeper insights and various missing value imputation strategies.

Topics covered

  • Summary Statistics
  • Missing Value Treatment
  • Dataframe analysis using groupby()
  • Advanced Data Explorations


Create informative visualizations using matplotlib

Write Python code using Python library: matplotlib to visualize data and represent it graphically.

Create informative visualizations using Seaborn

Write Python code using Python library: Seaborn to visualize data and represent it graphically. 

Using House Attributes and Sales Price, perform exploratory data analysis

House Attributes and Sales Price data. Use this data to explore more. Deep Dive into advanced explorations. Analyze and Visualize missing data, treat missing data to missing value imputation. Visualize data with

Read More
Note: These were the projects undertaken by students from previous batches.  

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The Course

Python is a rapidly growing high-level programming language which enables clear programs on small and large scales. Its advantage over other programming languages such as R is in its smooth learning curve, easy readability and easy to understand syntax. With the right training, Python can be mastered quick enough and in this age where there is a need to extract relevant information from tons of Big Data, learning to use Python for data extraction is a great career choice.

Our course will introduce you to all the fundamentals of Python and on course completion, you will know how to use it competently for data research and analysis. puts the median salary for a data scientist with Python skills at close to $100,000; a figure that is sure to grow in leaps and bounds in the next few years as the demand for Python experts continues to rise.

On completing this course, you will be competent in:- Using Jupyter Notebooks in Anaconda- Creating user-defined functions
- Manipulating & analyzing data
- Visualizing data using Python libraries like Matplotlib and Seaborn

Python programmers are in much demand and by the end of this course, you will be able to land a role as a Python developer or data science expert. You would have gained knowledge of the use of data science techniques and the Python language to build applications on data statistics and write reusable, testable and efficient code.

Tools and Technologies used for this course are-Python-Anaconda

There are no restrictions but participants would benefit if they have elementary programming knowledge and familiarity with statistics.

On successful completion of the course, you will receive a course completion certificate issued by KnowledgeHut.

Your instructors are Python experts who have years of industry experience. 

Finance Related

Any registration canceled within 48 hours of the initial registration will be refunded in FULL (please note that all cancellations will incur a 5% reduction in the refunded amount due to transactional costs applicable while refunding) Refunds will be processed within 30 days of receipt of the written request for a refund. Kindly go through our Refund Policy for more details.

The Remote Experience

In an online classroom, students can log in at the scheduled time to a live learning environment which is led by an instructor. You can interact, communicate, view and discuss presentations, and engage with learning resources while working in groups, all in an online setting. Our instructors use an extensive set of collaboration tools and techniques which improves your online training experience.

Minimum Requirements: MAC OS or Windows with 8 GB RAM and i3 processor.

Have More Questions?

Python for Data Science Course in Singapore

The national personification of Singapore is the Merlion and just like its mascot, the country too embodies diverse characteristics?that of a business leader, futuristic city with sci-fi architecture, mouth-watering delicacies, wide open spaces and an enviable waterfront. From being a fishing village to dominating Asia?s markets, Singapore has come a long way. The skyline today is dominated by skyscrapers that house some of the world?s most renowned companies including CISCO, OCBC, GE, Dell, Microsoft and top companies in the shipping, finance, oil-refining, and engineering sectors. Among its distinctions include being one of the world?s busiest port, top oil-refining centre, the largest oil-rig producer, ship repair services, and according to the World Bank one of the easiest places to do business. And if you think Singapore is all about work then you should know that it is also the world's second largest casino gambling market. Professionals who wish to thrive in their career would find that they can do well here, with certifications such as PRINCE2, PMP, PMI-ACP, CSM, CEH, CSPO, Scrum & Agile, MS courses and others. Note: Please note that the actual venue may change according to convenience, and will be communicated after the registration.
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