Python for Data Science Course

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

  • 32 hours of Instructor-led Training
  • Analyze and Visualize data with Python libraries
  • Analyze and Treat Missing Values
  • Perform in-depth Exploratory data Analysis with Hands-on Exercises
  • Get Free E-learning Access to 100+ courses

Description

Python has been widely accepted as the programming language of choice for high-level data processing because of its no-mess syntax, easy readability, and easy comprehension. Its numerous data structures, classes, nested functions, iterators, the flexible function calling syntax and extensive libraries make it apt for data analyzing, extracting information and making informed business decisions.

According to a survey by  Coding Dojo which analyzed job postings on several career websites, Python is, without argument, the most in-demand coding language in America. The popularity of data science in driving business has pushed the demand for Python experts and programmers. Keeping this in mind we have designed a Python course for you which will help you master the language and use it to develop powerful data statistics applications.

This course will walk you through Python basic programming and usage of critical libraries like Numpy, Pandas, Matplotlib, Seabon, and ggplot. Python for Data Science course prepares you with Python Programming capabilities for Data Manipulation, Exploratory Data Analysis and Data Visualization which are an absolute must for being a Data Science expert. Our intensive prep will help you clear any interview and land coveted positions. Python is a disruptive technology and mastering it can ensure that you land a lucrative job in the field of data science.

What You Will Learn

Prerequisites

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

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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

KnowledgeHut Experience

Instructor-led Live 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 support team 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 feedback on your final projects from professional developers.

Curriculum

Learning Objectives:

Learn how to install Python distribution - Anaconda, the basic data types, strings & regular expressions.

Topics Covered:

  • Install Anaconda
  • Data Types & Variables

Hands-on:

Install Anaconda - Python distribution.

Learning Objectives:

In this module you will learn to convert messy text into something useful. You will also learn to use regular expressions to utilize search methods and patterns.

Topics Covered:

  • String Operations
  • Uses of Regular Expressions
  • Methods of Regular Expressions
  • Commonly used Operators

Hands-on:

Write Python code to use regular expressions and implement search methods.

Learning Objectives:

Learn about the Data structures that are used in Python

Topics Covered:

  • Arrays
  • Lists
  • Tuples
  • Dictionaries
  • Sets

Hands-on:

Write Python Code to understand and implement Python Data Structures.

Learning Objectives:

Learn all about loops and control statements in Python.

Topics Covered:

  • For Loop
  • While Loop
  • Break Statement
  • Next Statements
  • Repeat Statement
  • if, if…else Statements
  • Switch Statement

Hands-on:

Write Python Code to implement loop and control structures in R.

Learning Objectives:

Write user-defined functions in Python. Learn about Lambda function and also the object-oriented way of writing classes & objects

Topics Covered:

  • Writing your own functions (UDF)
  • Calling Python Functions                 
  • Functions with Arguments
  • Calling Python Functions by passing Arguments
  • Lambda Functions

Hands-on:

Write Python Code to create your own custom functions without or with arguments. Know how to call them by passing arguments wherever required.

Learning Objectives: 

Gain knowledge on OOPs to code easily and efficiently. Learn to construct classes and define objects.

Topics Covered:

  • Introduction to Python Classes
  • Defining Classes
  • Initializers
  • Instance Methods
  • Properties
  • Class Methods and Data
  • Static Methods
  • Private Methods and Inheritance
  • Module Aliases and Regular Expressions

Hands-on:

Write Python code to construct a class and define objects.

Learning Objectives: 

Learn how to import datasets into Python. Also, learn how to write output into files from Python.

Topics Covered:

  • Reading files using Pandas library
  • Understanding function parameters
  • Writing files from Python
  • Reading files using Pandas library
  • Reading various other file types in python

Hands-on:

Write Python Code to read and write data from/to Python.

Learning Objectives:

Manipulate & learn to transform raw data using Pandas library. Learn to generate insights from your data.

Topics Covered:

  • Clean & Prepare Datasets
  • Data Transformations
  • Encoding

Hands-on:

Write Python code to manipulate data frames and churn insights using various python libraries.

Learning Objectives:

Learn to summarize dataset through descriptive statistics. Use a variety of measurements to better understand your data. Learn to treat missing values. Also, learn how to discover patterns in your data.

Topics Covered:

  • Summarize Data
  • Statistical analysis of Data
  • Extensive Data Exploration for deeper insights
  • Missing value treatment
  • Quality Analysis

Hands-on:

Write Python code to summarize dataset through descriptive statistics and treat the missing values after analysis.

Learning Objectives:

Master in a commonly used Python graphics module, Matplotlib. Learn to create charts such as histogram, pie-chart, box plots and so on using matplotlib.

Topics Covered:

  • Installing matplotlib
  • Importing matplotlib
  • Modules of matplolib: pyplot, image, animation
  • Charts using matplotlib: box plot, pie-charts, scatterplots, histogram, bar-chart

Hands-on:

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

Learning Objectives:

Learn how to use one of Python’s most convenient libraries, Seaborn, for data visualization. Build charts such as violin plots, scatterplot, heat-maps and so on using Seaborn.

Topics Covered:

  • Installing Seaborn
  • Importing Seaborn
  • Applications of Seaborn
  • Visualizing statistical relationships
  • Seaborn figure styles

Hands-on:

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

Learning Objectives:

Jump into an advanced visualization technique, that is ggplot in Python. Understand Grammar of Graphics and apply it to create charts.

Topics Covered:

  • Grammar of Graphics
  • Installing ggplot
  • Importing ggplot
  • Components of ggplot
  • Charts using ggplot: Bar charts, Scatterplots, Polar PlotsHands-on:: Write Python code using ggplot to visualize data and represent it graphically

Learning Objectives:

Learn to implement data analyzing methods, visualize the same and understand missing value treatment methods.

Topics Covered:

  • Checking missing values
  • Visualize data after analyzing
  • Methods to impute missing values

Hands-on:

Write Python code to analyze, visualize and treat missing values.

Learning Objectives:

Hands-on session on a real-life case study.

Topics Covered:

  • Real-Life Case Study

Hands-on:

Case Study: 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 various libraries. Gain deep insights on your data.

Projects

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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Faq

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. Payscale.com 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.

KnowledgeHut offers a 100% money back guarantee if the candidate withdraws from the course right after the first session. To learn more about the 100% refund policy, visit our Refund Policy.

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.

Certification FAQs

Data Science for Python

Python for Data Science is a course that will walk you through Python basic programming and usage of critical libraries like Numpy, Pandas, Matplotlib, Seabon, and ggplot. Python for Data Science course prepares you with Python Programming capabilities for Data Manipulation, Exploratory Data Analysis and Data Visualization which are an absolute must for being a Data Science expert. Our intensive prep will help you clear any interview and land coveted positions. Python is a disruptive technology and mastering it can ensure that you land a lucrative job in the field of data science.

Python for Data Science can be easy or difficult depending on your learning approach and technical expertise. Whether you are a novice or experienced programmer, getting trained under an expert Python for Data Science practitioner via live interactions can help reduce the learning curve and enrich your learning experience.

KnowledgeHut’s Python for Data Science course combines Immersive Learning approach with live, interactive sessions led by expert practitioners to help you upskill faster and easier. The course aims at refining your skills through actual projects, real-world case studies, hands-on exercises, and more.


To enroll, checkout our upcoming courses.

Yes, you can attend the Python for Data Science Course Online via KnowledgeHut. Our Python for Data Science Course is an online training program designed to improve your skills via fun engaging sessions lead by industry’s best, hands-on exercises, and simulated environment, among others.

Learn Data Science with Python

Python is a rapidly growing high-level programming language that helps one write clear programs at small and large scales. Python has a smooth learning curve, easy readability, and easy to understand syntax. So, with the right training, Python can be mastered quick enough. In this Digitized Era there is a rising need for data extraction, therefore, mastering Python can boost your career and widen your job prospects.

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. Payscale.com 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. 

You can learn the following in the Python for Data Science course:

  1. Basics of Python - Learn to install Anaconda and Python distribution 
  2. Python fundamentals - Explore Python language fundamentals, including basic syntax, variables, and types 
  3. Data Structures - Learn about the different data structures Python can handle. Create and manipulate regular Python lists, tuple etc. 
  4. Conditional Statements - Learn about control and loops statements 
  5. Object-Oriented Programming - User defined function, an object-oriented way of writing classes/objects, use functions, import packages 
  6. Analyzing Data - Manipulate and analyze a dataset in Python using Pandas 
  7. Python for advanced analysis - Build Numpy arrays, and perform interesting calculations 
  8. Data Visualization - Use various Python libraries to visualize data. Create and customize plots on real data 

Python for Data Science can be mastered in a matter of weeks. With the right training, Python can be mastered quickly and easily. Getting trained under an expert Python for Data Science practitioner can help reduce the learning curve and enrich your learning experience.

KnowledgeHut’s Python for Data Science course combines Immersive Learning approach with live, interactive sessions led by expert practitioners to help you upskill faster and easier. The course equips you with the in-demand Python skills through actual projects, real-world case studies, hands-on exercises, and more. 

You can learn Python for Data Science online via KnowledgeHut. The Python for Data Science course equips you with the necessary Python expertise to carry out various data-related functions. Our training sessions are made live and engaging via hands-on exercises, live projects, actual case-studies, expert guidance, and more.

You can start learning Python for Data Science with this foundational course. This course will walk you through Python basic programming and usage of critical libraries like Numpy, Pandas, Matplotlib, Seabon, and ggplot. Python for Data Science course prepares you with Python Programming capabilities for Data Manipulation, Exploratory Data Analysis and Data Visualization which are an absolute must for being a Data Science expert. Our intensive prep will help you clear any interview and land coveted positions. Python is a disruptive technology and mastering it can ensure that you land a lucrative job in the field of data science.

There are no Prerequisites for Python for Data Science Course. Data Science aspirants like you, regardless of your coding expertise or level of experience, can benefit from this course.

Python for Data Science Course

The following individuals can attend our Data Science Course:

  • Data science aspirants with the desire to learn essential skills. 
  • Those new to Python and looking for a more robust, structured learning program to upskill. 
  • Software or Data Engineers interested in learning Python for Data Science. 

Python Data Scientist

The top skills that a Python Data Scientist must have are:

  • How to use String and Regular Expressions 
  • Using Data Structures in Python 
  • Using Control and Loop Statements in Python 
  • Application of Functions and Classes in Python 
  • Object-Oriented Programming 
  • Data Manipulation Using Pandas 
  • Exploratory Data Analysis 
  • Data Visualization With Matplotlib 
  • Data Visualization With Seaborn 
  • Data Visualization with ggplot 
  • Analysis, Visualization and Treating Missing Values 

Here are the steps to launch a successful Data Science career with Python:

  • Choose a Python for Data Science Course that offers you a real-world view of working in Data Science and the opportunity to learn Python hands-on 
  • Attend the course and make sure you finish it 
  • Keep practicing and gain the confidence to work with Python 
  • Choose a Data Science role you like and learn all about it. Checkout some of our other Data Science courses that can help you grow in the role you choose to pursue 
  • Keep learning, keep-up with the latest trends and practices 
  • Join a peer group, expand your network, and connect with other Data Science practitioners 
  • Create a stellar portfolio and resume 
  • Find a mentor who can guide you in your Data Science journey

Jobs

Data Science has bagged the top spot in LinkedIn’s Emerging Jobs Report for the last three years. Thousands of companies need team members who can transform data sets into strategic forecasts. The average salary for a data scientist in the U.S. is $122,338 per year and according to the Bureau of Labor Statistics, the demand for data scientists is pegged to grow by 16% between 2020 and 2028, a rate that is faster than the average for all occupations.

As the field continues to evolve there is a growing demand for Data Science skills, including Python. The need for Python for Data Science professionals is rising worldwide, here are some of the top firms that are hiring today: 

  • Booz, Allen, and Hamilton 
  • Microsoft Corp 
  • Amazon.com Inc. 
  • Apple Computer, Inc  
  • Ford Motor Company  
  • International Business Machines (IBM) Corp 

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