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Data Science with Python Certification​

Data science using python

Data Science with Python is a scripting language that is high-level, interpreted, and interactive, and this become one of the most popular programming languages around the world. If we compare Python with other languages such as Java or C++, Python consistently outranks and outperforms these languages are in demand from businesses and job availability. The average Python developer makes over $100,000 – this number is only going to grow in the coming years.

The best part of Python?

Python is one of the easiest coding languages to learn right now. Even if you are not from coding background or are not familiar with the syntax of Python, still you will be able to learn it easily by just giving it the most attention. And by the time you finish this course, you’ll be an absolute pro at programming!

(12K+ Satisfied Learners)

Why learn Data Science with Python Training?

  • Ease of Learning.
  • Faster Development and Processing.
  • Powerful Packages.
  • Community Support.
  • Better Data Visualisation.
  • Compatible with Hadoop.
Python Institute’s certification not only provides a recognized benchmark of skills and knowledge which can be well incorporated into a company skills framework, but it also ensures that teams working on various IT projects are trained to consistent and expected levels of the desired skills.
Thanks to Python’s focus on simplicity and readability, it boasts a gradual and relatively low learning curve. This ease of learning makes Python an ideal tool for beginning programmers. Python offers programmers the advantage of using fewer lines of code to accomplish tasks than one needs when using older languages

Instructor -Led Online & Physical Classes

Batch Start DateClass TypeUpcoming SlotsTimingsLocation
12th May 2024OnlineSold Out
11:00 AM to 1:00 PMOnline
8th Jun 2024Online & OfflineSAT & SUN
Weekend Batch

20th Jul 2024Online & OfflineSAT & SUN
Weekend Batch


Start Your Course Now

INR 25,000/-+GST
INR 20,500/- + 18% GST

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Data Science with Python Course Content

For the curriculum, you will cover  in this course, click on the tab to check the detailed content

Module 1:- Installing & Running Python

  • Python 2.7 vs Python 3
  • Local Environment Setup
  • Installing Python on different platforms(Windows and Linux)
  • Python Interpreter and Python Interactive Shell
  • Python IDE(Pydev, Pycharm,VIM)

Module 2:- Python Introduction

  • Python Overview
  • History Of Python
  • CPython, Jython, PyPy
  • Python Features
  • Areas Of Application of Python
  • Understanding More About Python
  • Writing your First Python Program
  • Interactive Mode Programming
  • Script Mode Programming
  • Dir and help: Getting help from the Python interpreter.

Module 3:- Python Syntax ,Keywords and Operators

  • Python Identifiers
  • Various Operators and Operators Precedence
  • Reserved Words,Lines and Indentation
  • Multi-Line Statements,Quotation in Python
  • Comments in Python,Using Blank Lines
  • Command Line Arguments
  • Python Input/Output:Using the Print Function
  • Getting Input from User
  • Python Basic Data Types And Variables
  • Binary, octal and hexadecimal numbers
  • Convert one data type to another

Module 4:- Expressions, Statements, Variables, Strings

  • Working With Numbers
  • Working With Booleans
  • Math library and its various operations
  • Working with Strings
  • String types and formatting
  • String Operations and Task
  • Program to find duplicate characters in a String.
  • Program to reverse a string
  • Program to check if String is Palindrome
  • Program to remove a newline in Python

Module 5:- Python Data Types: List,Tuples,Dictionaries

  • Python Lists, Tuples, Dictionaries
  • Accessing Values
  • Basic Operations
  • Indexing, Slicing, and Matrixes
  • Built-in Functions & Methods
  • Exercises on List, Tuples And Dictionary
  • Remove Duplicate from Lists
  • Program to find the index of an item of a tuple
  • Python program to convert a list to a tuple
  • Python program to reverse a tuple
  • Program to convert a tuple to a dictionary

Module 6:- Making Decisions – if Statements

  • The Relational Operators
  • The Logical Operators
  • Simple if Statement,if-else Statement
  • If-elif Statement
  • More Advanced If, ElIf & Else Processing

Module 7:- Loop Control

  • Introduction To while Loops
  • Count-Controlled while Loops
  • Event-Controlled while Loops
  • Using continuE,Using break
  • Introduction To for Loops
  • For loops with files,list,tuples and dictionaries

Module 8:- Iterators

  • Understanding Iterators
  • Using iter And next
  • Iterators And Dictionaries
  • Other Iterators

Module 9:- Functions And Scopes

  • Introduction To Functions – Why
  • Defining Functions
  • Calling Functions
  • Functions With Multiple Arguments
  • Predicate Functions,Recursive Functions
  • Function Objects,Generators,Decorators
  • Anonymous Functions, Higher-Order Functions
  • Scope , Global Scope, Local Scope , Nested Scope

Module 10:- Modules and Packages

  • Using Built-In Modules
  • User-Defined Modules
  • Module Namespaces
  • Installing and Uninstalling a package
  • Package vs Library vs Module

Module 11:- File I/O

  • Printing to the Screen
  • Reading Keyboard Input
  • Opening and Closing Files
  • Open Function,file Object Attributes
  • close() Method ,Read,write,seek
  • Rename,remove,
  • Mkdir,chdir,rmdir

Module 12:- Error And Exceptional Handling

  • Exception Handling, Assertions: The assert Statement
  • What is Exception, Handling an exception
  • The except Clause with No Exceptions, the try-finally Clause
  • The argument of an Exception, Raising an Exceptions
  • User-Defined Exceptions 

Module 13:- Regular Expression

  • Matching and Searching- match() and search() Functions
  • Search and Replace
  • Regular Expression Modifiers
  • Regular Expression Patterns
  • Regular Expression Quantifiers

Module 14:- Introduction to Data Science and Machine Learning

  • Matching and Searching- match() and search() Functions
  • Search and Replace
  • Regular Expression Modifiers
  • Regular Expression Patterns
  • Regular Expression Quantifiers

Module 15:- Tools & Languages available

  • Python .R
  • Python & R Differences
  • Python Distribution
  • Python tools for Data Science
  • Anaconda Installation
  • Jupiter Notebook Usage and Examples

Module 16:- Numpy

  • Introduction to Numpy. Array
  • Creation,Printing Arrays
  • Basic Operations- Indexing, Slicing and Iterating
  • Shape Manipulation – Changing
  • Shape,stacking and spliting of array
  • Random number

Module 17:- Pandas, Matplotlib and Seaborn


  • Introduction to Pandas
  • Importing data into Python
  • Pandas Data Frames,Indexing Data
  • Frames ,Basic Operations With Data
  • frame,Renaming Columns,Subletting and filtering a data frame.


  • Introduction,plot(),Controlling Line
  • Properties,Working with Multiple
  • scatter, hist, bar, piechart
  • subplot, titles, axis, colormap
  • Figures,Histograms


  • Plot for categorical and numerical data
  • Plot for categorical vs numerical, numerical vs numerical, categorical vs categorical
  • distplot, jointplot, boxplot, barplot, countplot, violinplot, swarmplot

Module 18:- Exploratory Data Analysis

  • Data Manipulations and Wrangling
  • Drawing Insights and Completing analysis
  • Imputing NA values


✔️ 38 Hours / 19 Sessions
✔️ Per Session for 2 Hours
✔️ Practice Hours

We have included real-life examples and case studies in our course. Complete written notes and code for you to read and refer

Projects for you to complete throughout the course. These provide a challenge and an opportunity for you to apply your learning.

In a set of the time period, you will be having access to getting support from our expert

After completing your course, we will provide you with a Course Completion Certificate

You will get 100% job assistance according to your CTC, Experience and Present skills

Need more details about the course, let’s connect with our experts

Let’s Get Our Expert’s Guidance

    How, Data Science is having Best Career Opportunities?

    Skills in Demand

    Data science continues to evolve as one of the most promising and in-demand career paths for skilled professionals. Today, successful data professionals understand that they must advance past the traditional skills of analyzing large amounts of data, data mining, and programming skills. In order to uncover useful intelligence for their organizations, data scientists must master the full spectrum of the data science life cycle and possess a level of flexibility and understanding to maximize returns at each phase of the process.

    Employability Increases

    Companies are giving preference to those candidates who have good skills in data science and that too using Python.  Candidates who have good command in Microsoft Excel, VBA, My SQL & Power BI, Tableau, Python. Many companies heavily depend on these programs for Data Analysis along with visualization.

    Job opportunities on the rise

    Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world’s most interesting problems!

    Most Frequent Questions and Answers

    Those who are interested in Data Science and wants to start their career as Data Scientist. Anyone who is particularly interested in big data, machine learning, and data intelligence

    Of course, you can learn Python without having any coding background. We start Python learning from scratch so that we can build a strong fundamental of the application and at an advanced level you can grasp it easily. And obviously, you need a lot of practice to be a pro.

    Though we have so many reasons to join us, let us highlight the main points:-

    1. After completing the course you will get 3 months of support time period extra to revise the sessions which are not cleared to you, any problem you are not able to solve that you can take our team’s help
    2. We provide video recordings if any of the reason you skip your session
    3. We have well-experienced trainers to teach our students
    4. Project-based training / unlimited examples to make you understand about the subject / Case Studies after every session / Job Support and many more

    Yes, of course, you will be getting “Completion Certificate” 

    • Start at zero and become an expert whilst learning all about the inner workings of Python.
    • Learn how to write professional Python code like a professional Python developer.

    • Embrace simplicity and develop good programming habits.

    • Improve your Python code with formatters and linters

    • Extract information from existing websites using web scraping.

    • Learn to interact with REST APIs to fetch data from other web applications.

    Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world’s most interesting problems!

    Student Reviews

    ATH is a very good place for learning many advanced courses in IT for working professionals. The faculties are very supportive and clearing the doubts. Felt happy to join ATH, Students also need to be more proactive in learning and solving the assignments which helps them a lot. Thank you ATH Regards Krishna Murthy KS
    ATH student review
    Krishna Murthy
    Junior Data Scientist

    I opted for Data Science Using Python course from ATH and after the course I can very well say I have hands-on experience in Pthon, SQL and many more. If you are in search of a Data Science Course then this is the place to learn. Not only this they provide Job Assistance too. Highly highly recommend it! Thank you ATH team!
    Enna Tewatia
    Data Scientist, Marketing & Online

    Highly recommended!! ATH is really helpful in keeping pace with changing technolgy. The team is excellent and content and teaching methodology is presented keeping in view the pace and understanding of its audience.
    Sonia Loomba
    Enterprise Data Scientist.

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