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Python for Data Science

Python for Data Science

Learn About Python Libraries that Help Store, Manipulate, and Get Insights from Data

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Python for Data Science

Prerequisites for Python for Data Science Course

Prerequisites and Eligibility
  • Basic computer knowledge
Prerequisites
  • 450,000+
    Professionals Trained
  • 250+
    Workshops Every Month
  • 100+
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Highlights of Python for Data Science Course

Become an Expert Data Scientist

17+ Hours of 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

Python is one of the easiest yet powerful programming languages. Learn the language designed to be highly readable and use 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.

Learn to use Python to implement the machine learning algorithms for prediction. Python's vast set of libraries for natural language processing, speech recognition, and computer vision makes it the primary choice in the domain of Artificial Intelligence. This course is primarily designed with the "learn by doing" philosophy. A simplified explanation of the topics, real-world analogies, codes being built from scratch, exhaustive demonstrations, and numerous hands-on practice sessions will equip the learner with the necessary knowledge of Python.

WHY KNOWLEDGEHUT for Python for Data Science

Get the KnowledgeHut Advantage

Learn by Doing

Our immersive learning approach lets you learn by doing and acquire immediately applicable skills.

Real-World Focus

Learn theory backed by real-world case studies and exercises, and get productive from the get-go.

Industry Experts

Get trained by leading practitioners who share best practices from their experience across industries.

Curriculum Designed by the Best

Our Data Science advisory board regularly curates best practices to emphasize real-world relevance.

Continual Learning Support

Webinars, e-books, tutorials, articles, and interview questions - we're with you in your learning journey!

Exclusive Post-Training Sessions

Six months of post-training mentor guidance to overcome challenges in your Data Science career.

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Python for Data Science Course Reviews

Our Learners Love Us

Great experience

Completed my training and certification through Knowledge Hut last week. It was a great experience. The Trainer was knowledgeable and able to resolve all my queries. The entire training was interactive. I enjoyed the entire session.

Sachin Garg
Sachin Garg
Data Analyst
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Great platform

Knowledge hut has been a great platform in facilitating certification trainings. Also this was one training in my life I would say I was never bored and had great hands on experience. Keep up the good work. Also they are very flexible with schedules and user convenience.

Divya Ramesh
Divya Ramesh
Programmer
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Wonderful training experience

Wonderful training experience with KnowledgeHut trainer. The process for course registration is very smooth and easy. The course material and mock papers are very useful. Thank you KnowledgeHut.

Virupakshappa N M
Virupakshappa N M
IT Professional
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Interactive sessions

I attended a training session with knowledge hut and like the programs they offer. The training session was interactive and teacher was skilled in engaging and keeping the session interactive. Thank you

Garima Verma
Garima Verma
Data Scientist
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Great experience

I really had a great experience attending the workshop for two days. The maximum syllabus was covered and a lot of important topics and questions were answered. great mentorship. Worth the session.

Prianca Oza
Prianca Oza
Business Analyst
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Python for Data Science Syllabus

Curriculum

1. Introduction to Python

Learning Objective:

Get an introduction to working with Python.

Topics:

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

2. Code and Data

Learning Objective:

Learn coding in Python to manage data.

Topics:

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

3. Building Blocks

Learning Objective:

Explore the components of working with Python.

Topics:

  • Introduction to Building Blocks
  • Data Types
  • Arithmetic Operators
  • Lists Basics
  • Important Functions and Features

4. Strings

Learning Objective:

Learn how to work with strings in Python.

Topics:

  • Introduction to Strings
  • Creating and Indexing
  • Negative Indexing, Slicing and Stepping
  • Immutability Concept
  • Important String Functions

5. Data Structures

Learning Objective:

Learn about the different data structures in Python.

Topics:

  • Introduction to Data Structures
  • Data Structures
  • Lists
  • List Functions - Part 1
  • List Functions - Part 2
  • Tuples
  • Sets

6. Flow Control

Learning Objective:

Learn to use conditional statements and loops in Python.

Topics:

  • Introduction to Flow Control
  • Conditional Statements
  • if elif else
  • other operators
  • While statement
  • for with sequences

7. Functions

Learning Objective:

Learn functions in Python and how to use them.

Topics:

  • Introduction to Function
  • User Defined Functions
  • Passing Parameters
  • Return Values

8. Modules

Learning Objective:

Explore modules in Python.

Topics:

  • Modules Overview
  • Introduction to Modules
  • Installing Modules
  • Fetching Modules
  • Important Modules and Packages

9. Files

Learning Objective:

Learn how to use files in Python.

Topics:

  • Introduction to Files
  • What are Files?
  • Opening and Reading Text Files
  • Different Modes of Opening Files
  • Reading & Writing into Text Files

10. NumPy

Learning Objective:

Explore how to use NumPy.

Topics:

  • Introduction to NumPy
  • What is NumPy?
  • Creating & 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


What You'll Learn in the Python for Data Science Course

Learning Objectives
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 text pad, 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 analyze 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.

Who Should Attend the Python for Data Science Course

Who This Course Is For
  • Data Scientists
  • Data Analysts
  • Individuals who have no prior programming experience in coding
  • Intermediate level professionals using Python for their tasks
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Python for Data Science FAQs

Frequently Asked Questions
Course Overview

1. What is Python for Data Science?

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.

2. What is Python for Data Science course?

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.

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