Python for Data Science

Learn about Python libraries that help in storing, manipulating, and getting insights from data

  • Learn from the leading industry experts with experience 
  • Get practical exercises to supplement theoretical learning 
  • Learn advanced tools to analyze and interpret data 
  • 400,000 + Professionals trained
  • 250 + Workshops every month
  • 100 + Countries and counting

Become an Expert Data Scientist

Python is one of the easiest yet powerful programming languages. Learn the language designed to be highly readable and uses English keywords frequently. Python's efficient data structures make it the first choice for analyzing data. Python helps analyze and visualize data in a convenient form that is easy to understand and aids in decision making.

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Highlights

  • 24 Hours of Live, Interactive, Trainer-Led Sessions 

  • 48 Quizzes and 188 Questions 

  • 13 Hours of Hand-on Training with Python 

  • 1 Real World Project that Adds to your Portfolio

  • Get Mentored by Experts with Industry Experience  

  • Gain the Skills to Become an Expert Data Scientist  

Data Scientists with Python Skills are in Demand

python-for-data-science-certification-training

Learn Python and practice using Python code and libraries to analyze, interpret, and visualize data. Enable superior data-driven decision-making by identifying trends, threats, and opportunities. There is a great deal of demand for skilled Data Scientists. Python is the language of choice for most Data Scientists because of the Python libraries available. 

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The KnowledgeHut Advantage

The most effective project-based immersive learning experience

Immersive Learning

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  • On-demand videos
  • Guided hands-on exercises
  • Auto-graded assessments and recall quizzes
  • Assignments and projects

Learn by Doing

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  • Learn to code. By actually coding.
  • Get project-ready with work-like experiences.
  • Learn on the job, like devs in tech companies.

Cloud Labs

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  • Access fully provisioned dev environment.
  • Virtual machine spinned up in minutes.
  • Write code right in your browser.

Outcome-Focused

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  • Get advanced learner insights.
  • Measure and track skills progress.
  • Identify areas to improve in.

Blended Learning

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  • On-demand, self-paced learning anytime.
  • Code review sessions by experts.
  • Access to discussion forums, community groups.
Prerequisites

Python for Data Science Prerequisites

  • Basic computer knowledge 

Who Should Attend the Course

Data Scientists

Data Analysts

Individuals who have no prior programming experience in coding

Intermediate level professionals using Python for their tasks

Schedules

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What You Will Learn

Python Coding

Learn to gain a complete understanding on the approach to be taken for coding in Python

Problem Definition

Convert real time problems into programming data that can be analyzed using Data Science

Data Management

Convert actual data from various sources like textpad, Excel, CSV into Python data structures  

Regular Expressions

Understand how to apply regular expressions to extract out relevant information from text files  

Data Analysis

Organize, interpret, and anaylze the data into useful information that provides context for the data 

Visualization

Learn how to graphically represent data for visual inferences that makes it easy to identify patterns 

Skills You Will Gain

Using data with operators and functions

Accessing, indexing, and slicing strings and other data

Using various data structures in different contexts

Implementing decision making and flow control

Making code reusable using functions and modules

Using regular expressions to extract relevant data

Using Pandas and DataFrames for organizing & filtering data

Generating statistical inferences using Pandas and NumPy

Using NumPy for numerical and mathematical computations

Advanced analytics techniques with Pandas

Visualization with matplotlib and seaborn

Visual concepts of Statistics

Transform Your Workforce

Enable Better Data Driven Decisions

Empower your team with the latest Python skills to gather insights from advanced data analytics using Python. 

  • Leverage Immersive Learning  
  • Get Your Teams Project-Ready 
  • Align Skill Development to Your Most Important Objectives 
  • Customized Corporate Training Programs 

500+ Clients

Curriculum

Learning Objective

Get an introduction to working with Python  

Topics
  • Python for Data Science 
  • Installation and Setup 
  • Hello World 

Learning Objective

Learn coding in Python to manage data 

Topics
  • What is Code and Data? 
  • Creating Data 
  • Using Data with Code 
  • Syntax and Naming Conventions 

Learning Objective

Explore the components of working with Python 

Topics
  • Data Types 
  • Arithmetic Operators 
  • Lists Basics 
  • Important Functions and Features 
4.

Learning Objective

Learn how to work with strings in Python 

Topics
  • Creating and Indexing 
  • Negative Indexing, Slicing, and Stepping 
  • Immutability Concept 
  • Important String Functions  

Learning Objective

Learn about the different data structures in Python 

Topics
  • Data Structures 
  • Lists 
  • List Functions – Part 1 
  • List Functions – Part 2 
  • Tuples 
  • Sets 
  • Dictionaries 

Learning Objective

Learn to use conditional statements and loops in Python 

Topics
  • Conditional statements 
  • If else 
  • Other operators 
  • While statement
  • For with sequences 
  • For with range 

Learning Objective

Learn functions in Python and how to use them  

Topics
  • User Defined Functions 
  • Passing Parameters 
  • Return Values 
8.

Learning Objective

Explore modules in Python 

Topics
  • Introduction to Modules 
  • Installing Modules 
  • Fetching Modules 
  • Important Modules and Packages 
9.

Learning Objective

Learn how to use files in Python 

Topics
  • What are Files? 
  • Opening and Reading Text Files 
  • Different Modes of Opening Files 
  • Reading and Writing into Text Files 
10.

Learning Objective

Explore how to use NumPy

Topics
  • What is NumPy? 
  • Creating and using NumPy arrays 
  • NumPy array attributes 
  • Array Indexing and Slicing 
  • Array Operations – Part 1 
  • Array Operations – Part 2 
  • Different Ways of Creating Arrays 
  • Random Number Generation 
11.

Learning Objective

Learn how to use Pandas in Python 

Topics
  • Introduction to Pandas 
  • Reading various file formats 
  • Creating Pandas Series and DataFrames 
  • Series Operations 
  • DataFrame Operations – Part 1 
  • Dataframe Operations – Part 2 

Learning Objective

Learn about RegEx, meta characters, and special sequences. 

Topics
  • Introduction to RegEx 
  • Meta characters – Part 1 
  • Meta characters – Part 2 
  • Special sequences – Part 3 
  • Special sequences – Part 4 

Learning Objective

Understand visualization in Python 

Topics
  • Introduction to visualization 
  • Basic plots 
  • Sub plots 
  • Bar, pie, histogram, and scatter 
  • Plots using Pandas  

FAQs

Training FAQs

This training is designed to help you use Python effectively in Data Science projects. By the end of this course, you will:

  • Gain a complete understanding of the approach to coding 
  • Convert real-time problems into programming data  
  • Convert actual data from various sources like textpad, excel, CSV into Python data structures  
  • Apply regular expressions to extract relevant information from text files 
  • Organize, interpret, and analyze the data into useful information that provides context for the data 
  • Graphically represent data for visual inferences 

You will gain skills to: 

  • Use data with operators and functions 
  • Access, index and slice strings and other data 
  • Understand and use various data structures in different contexts 
  • Implement decision making and flow control 
  • Make code reusable using functions and modules  
  • Read data from text files and extract relevant information using regular expressions  
  • Use pandas, DataFrames for organizing & filtering data from Excel, CSV etc. 
  • Generate statistical inferences using Pandas and NumPy 
  • Use NumPy for numerical and mathematical computations 
  • Learn advanced analytics techniques with Pandas 
  • Discover visualization with matplotlib and seaborn 
  • Visually understand concepts of Statistics  

By the end of Python certification training for Data Science, you would have gained knowledge of how to work with Python and Data Science. 

To take part in the Python certification for Data Science course you only need basic computer knowledge. It will be beneficial if you have programming knowledge, but that is not a requirement.  

Yes, KnowledgeHut offers this Python for Data Science professional certification in the online format. 

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

Your instructors for the Python for Data Science training are experts in Python and Data Science who have many years of industry experience. 

Workshop Experience

Currently Python for Data Science certification training course is offered online as Live, interactive, trainer-led sessions where you will get to learn directly from the trainer with opportunities to discuss and clear doubts. 

Our instructors are experts in Python and Data Science to lead these sessions. They also have hands-on experience and will be able to tell you the practical aspects of what you are learning. This best online course for learning Python for Data Science will help you master Python and Data analysis skills.  

Our Python for Data Science classes are delivered through live interactive virtual classrooms and can be structured according to the requirements of the course. 

Our training focuses on interactive learning. Most class time is dedicated to hands-on exercises, lively discussions, and team collaboration, all facilitated by the trainer who is an experienced expert. In the Python for Data Science full course, the focus is on finding practical solutions to real-world scenarios in various project environments, both big and small. 

In an online classroom for Python for Data Science essential training online course, students can log in at the scheduled time to a live learning environment that 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 for the course use an extensive set of collaboration tools and techniques which improve your online training experience. 

Internet Connectivity (2Mbps Link) and Minimum Requirements: Workstation or laptop with 8GB+ RAM, 512GB+ hard-disk and 2GHz+ processor speed]

Software requirements:

  • Anaconda Distribution with Python 3.7+ 
  • Python packages: pandas, matplotlib, seaborn, sklearn, nltk, jupyter 

Yes, you can switch your start date for the Python for Data Science certificate course with prior notice of at least 24 hours and subject to availability in the desired batch. 

Additional FAQs

Course FAQs

Python is one of the most popular programming languages and it is being used extensively for Data Science. Python for Data Science refers to those features of Python that come in handy for Data Science. 

The Python for Data Science course trains professionals in using Python to achieve Data Science related objectives like managing data, visualizing it, and extracting insights out of it.  

Python is one of the most preferred tools for a Data Science professional. It can be used in diverse ways to meet a variety of challenges that a professional may face in Data Science. 

In the best course for Python for Data Science You will learn Python for Data Science by first understanding the basics of Data Science and Python. After you have acquired a clearer view of it, you will learn to use Python and its components to address Data Science related challenges. 

Python is a language that is diverse and can be used for a wide range of uses. While learning Python for Data Sciences you only need to learn the parts that are useful to you including the Python libraries that are used in Data Science. 

An understanding of Python fundamentals will open you to possibilities of the various ways you can use Python to manage data, visualize it, and see patterns and trends.   

PyCharm, Visual Studio Code, Atom, Spyder etc., are IDEs that are popularly used for Python in the Data Science discipline.  

Training FAQs

Once you are familiar with Data Science concepts, you can learn how to use Python to achieve your goals and explore the libraries in it that are relevant to Data Science.

The time it takes for you to learn Python for Data Science will depend on your current level of understanding of both Data Science and Python. Typically, it takes a couple of months to get a good handle on using Python for Data Science. 

The most effective way to practice Python for Data Science is to work on active Data Science projects to try out your newly acquired skills. The best course to learn Python for Data Science will give you plenty of chances to practice what you learn. 

Python is one of the easier languages to learn. If you are familiar with Data Science concepts using Python for Data Science will not be too hard.  

The best way to practice Python for Data Science is to do it on live projects and understand how it works in the real world. 

It is essential for you to understand Data Science concepts to be able to apply Python and Python libraries related to Data Science.  

What Learners Are Saying

A
Anubhav Ingole Senior Data Scientist
4

At KnowledgeHut, I had one of my best educational experiences. The course is extensive and contains many materials, including videos, PPTs, and PDFs. In addition, all the trainers and the support staff were incredibly accommodating and accessible.

Attended Data Science with Python Certification workshop in August 2022

A
Amanda H Senior Front-End Developer
5

You can go from nothing to simply get a grip on the everything as you proceed to begin executing immediately. I know this from direct experience! 

Attended Full-Stack Development Bootcamp workshop in July 2022

E
Eden Knight Data Analyst
4

I successfully transitioned my career I am a SDE who was unhappy with my job. I took a giant leap of faith and transitioned to a Data Science career after completing KnowledgeHut’s Data Science bootcamp. I love the challenges and the paycheck! Thank you Knowledgehut for giving me the confidence that I could do it. All of you who are not too happy with your present role- there's a whole world of opportunity out there. Take the first step.

Attended Data Science Bootcamp workshop in July 2021

D
Dave Murphy Web Developer
5

Best quality in the market today In today’s world, Data science is among the best career options for an IT professional. Having already done a bunch of courses from KnowledgeHut, I was already sure of the quality of the training. And I was not disappointed. Their Data Science Bootcamp was an intensive yet refreshing course that has made me very confident to look for a job as an analyst. Thank you KnowledgeHut!

Attended Data Science Bootcamp workshop in July 2021

N
Neil Radia Project Manager
4

5 stars What a totally awesome Data Science bootcamp! I tried learning on my own through text books and online material, but it was such a struggle as I had no one to clear my doubts. Knowledgehut has brought out a totally different and interactive, comprehensive, logical systematic approach to the subject that made it super fun to learn. Love all your courses(This is my fifth!).

Attended Data Science Bootcamp workshop in July 2021

B
Ben Johnson Developer
5

The Backend boot camp is a great, beginner-friendly program! I started from zero knowledge and learnt everything through the learn-by-doing method. 

Attended Back-End Development Bootcamp workshop in July 2021

E
Emma Smith Back End Engineer
5

KnowledgrHut’s Back-End Developer Bootcamp helped me acquire all the skills I require. The learn-by-doing method helped me gain work-like experience and helped me work on various projects. 

Attended Back-End Development Bootcamp workshop in May 2021

K
Kayne Stewart slavsky Project Manager
5

The course materials were designed very well with all the instructions. The training session gave me a lot of exposure to industry relevant topics and helped me grow in my career.

Attended PMP® Certification workshop in June 2020

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