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

FAST-TRACK YOUR DATA SCIENCE CAREER

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 workforce with the right development skills and ensuring that best practices are followed.  

This immersive and interactive workshop with a path breaking curriculum, capstone project and guided mentorship is your ticket to launch a career as a Data Analyst. Laying emphasis on project and 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 the 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

Prerequisites

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

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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 on your final projects 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

Curriculum

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

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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