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Data Analytics with Python – Uses, Certifications, And More

Are you interested in a course that will help you boost your confidence as well as skills? Do you like tech-based courses and want to become a pro in this field? You can join Data Analytics with Python course. It has a great future in today’s world. People want to join a course that helps them develop their knowledge and skill for their future and tech-based courses give advantages. Big industries hire data analysts to boost their business precision. If you are the one who knows how to analyze and visualize data with the help of a programming language like Python, you are in a great position to be hired by those big companies. Python is a programming language that is emerging in the world of coding. It is used in coding and software development. In this article, we have discussed the definition of data analysis, the definition of Python, and top courses that offer data analytics with Python. Hope this article will help to find your queries and take you in a good state of mind by solving your questions. Let’s check the details.

Data Analytics With Python

What is Data Analysis?

There is a plethora of data on the internet every day. In a business or firm, these data are not used by them. In this case, data analysis is significant. Data analysis is a process of collecting useful and helpful data from those huge unintelligible and unimportant datasets. With the help of analyzation of data, raw data is transformed into intelligible and rational data to find business trends for future betterment in a business or firm.

What is Python?

Python is a high-level computer programming language used to build websites and software, and analyze datasets. It helps analyze and visualize data with the help of various libraries and find trends in a business for future precision.It has simple, easy-to-learn syntax. It is readable and it reduces the cost of program maintenance.

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Why Data Analytics Using Python?

  • Python is used by statisticians, engineers, and scientists to perform data analytics in a business for their future precision.
  • Python is easy to learn and understand. It has a simple syntax.
  • The programming language is scalable, flexible, and readable.
  • It has a vast collection of libraries for numerical computation and data manipulation like NumPy, Pandas, Matplotlib, SciPy, Scikit-Learn, etc.
  • Python provides libraries for graphics and data visualization to find patterns in a business or firm.
  • It helps solve many kinds of queries.

Python Libraries for Data Analytics

Python libraries are:

  • NumPy: NumPyprovides numerical computing tools. NumPy is useful for Linear algebra.
  • Pandas: It is one of the most well-known libraries. It performs mathematical operations, and manipulates data.
  • Matplotlib: Matplotlib library is used for creating interactive visualizations of the data.
  • SciPy: SciPy librarycontains modules for optimization, linear algebra, integration, signal, and image processing.
  • Scikit-Learn: Scikit-Learn allows you to build regression, classification, and clustering models.

Read in-depth:

Top 9 Data Analytics with Python

1. IIM SKILLS Data Analytics Course

IIM SKILLS offers Data Analytics course With Python for students as well as experienced people. The course will take students from the basics of data analysis. Students will come to know how to build and evaluate data models. It is an essential skill for data analysts to analyze data with Python.

Modules Covered

Module NameImportant Topic
Module 1: Basic and Advance Excel
Introduction to Data Handling
Data Manipulation Using Functions
Data Analysis and Reporting
Data Visualization in Excel
Overview of Dashboards
Module 2: Visual Basic Application
Introducing VBA
How VBA Works with Excel
Key Components of Programming Language
Programming Constructs in VBA
Functions & Procedures in VBA
Objects & Memory Management in VBA
Error Handling
Controlling Accessibility of Your Code
Communicating with Your Users
Module 3: SQL
Basics RDBMS Concepts
Utilizing the Object Explorer
Data Based Objects Creation (DDL Commands)
Data Manipulation (DML Commands)
Accessing Data from Multiple Tables Using SELECT
Optimizing Your Work
Module 3.1: SQL Server Reporting Services
Basics of SSRS
Creating Parameters
Understanding Visualization
Creating Visualization Using SSRS
Module 3.2: SQL Server Integration Services
Understanding Basics of SSIS
Understanding Packages
Creating Packages to Integrate
Creating Project Using SSIS
Module 4: Power BI
Data Preparation and Modeling
Data Analysis Expressions (DAX)
Reports Development (Visuals in Power BI)
Module 5: Data Analytics Using Python
Introduction to Basic Statistics
Introduction to Mathematical Foundations
Introduction to Analytics & Data Science
Python Essentials (Core)
Operations with NumPy (Numerical Python)
Overview of Pandas
Cleansing Data with Python
Data Analysis Using Python
Data Visualization with Python
Statistical Methods & Hypothesis Testing
Module 6: Tableau
Getting Started
Data Handling & Summaries
Reports Development (Visuals in Tableau)
Module 7: R For Data Science
Data Importing/Exporting
Data Manipulation
Data Analysis
Using R with Databases
Data Visualization with R
Introduction to Statistics
Linear Regression: Solving Regression Problems
Module 8: Alteryx
Overview of the Alteryx Course and Fundamental Concepts
Using the Select Tool to Rename Fields, Change the Data Type
Understanding the User Environment and Alteryx Settings
Filtering Data/Data Processing
Blending/Joining Data from Different Sources
Data Cleansing
Impute Values
Random Sample
  • Course Name – Data Analytics Course 
  • Course Duration – 6 months of Training + 2 Months  Internship (Non-Paid)
  • Course Fee – INR 49900 + Taxes

Key benefits of the course

  • Import data from multiple sources.
  • Create meaningful data visualization.
  • Predict future trends from data by developing linear, multiple, polynomial regression models & pipelines.
  • Work with several open-source Python libraries, including Pandas and Numpy to load.
  • Manipulate, analyze, and visualize datasets
  • LMS Access Free for session recordings and study materials
  • Soft skills training
The tools covered in the course include 
  • Python
  • Excel
  • Power BI
  • Tableau
  • SQL
  • Alteryx
  • R

You will learn the below-mentioned skills after completing the course

  • Develop Python code for cleaning and preparing data for analysis – including handling missing values, formatting, normalizing, and binning data.
  • Perform data analysis and apply analytical techniques to real-world datasets using libraries such as Pandas, and Numpy.
  • Data frames, summarize data, and create data pipelines.
  • Build and evaluate regression models using the machine learning scikit-learn library.
  • Predictive Modelling
  • Python Programming
  • Data Analysis
  • Data Visualization
  • Model Selection

Professional Courses from IIM SKILLS

Contact: +919580740740, [email protected]

Dig in here and find the advanced courses:

2. Udemy

Udemy offers online Data Analytics with Python course.

Topics covered in this course

  • Introduction to Python, Numpy, and Pandas
  • Working with Data:
  • Part 1 Includes (Reading and Writing Text Files, JSON with Python, HTML with Python, and Microsoft Excel files with Python)
  • Part 2 Includes (Merge, Merge on Index, Concatenate, Combining DataFrames, Reshaping, Pivot Tables, Duplicates in DataFrames, Mapping, Replace, Rename Index, Binning, Outliers, Permutation)
  • Part 3 includes (DataFrames, Series, Aggregation, Splitting Applying and Combining, Cross Tabulation)

Data Visualization

  • Introduction to Data Projects
  • Titanic Project 1-4

Introduction to Data Project

  • Stock Market Analysis Part 2
  • Data Project – Stock Market Analysis
  • Stock Market Analysis
  • Data Projects
  • Election Analysis
  • Data Project
  • Election Analysis

Introduction to Machine Learning

  • Linear Regression 1-4
  • Logistic Regression1-4
  • Multi-Class Classification1 & 2
  • Support Vector Machines1 & 2
  • Naive Bayes 1 & 2
  • Decision Trees and Random Forests
  • Natural Language Processing 1-4

Key benefits of the course

  • You will possess an intermediate skill level in Python programming.
  • You will learn to use the Jupyter Notebook Environment.
  • You will learn how to use the Numpy library to create and manipulate arrays.
  • You will have access to use the Pandas module with Python to create and structure data.
  • You will learn how to work with various data formats within python, including HTML, and MS Excel Worksheets.
  • You can create data visualizations using Matplotlib and the Seaborn modules with python.
  • You will develop a portfolio of various data analysis projects.

You will learn the below-mentioned skills after completing the course

  • The learners will comprehend how to program in Python.
  • You will know how to create arrays using Python.
  • You will understand how to use Pandas to analyze and visualize data.
  • The students can know how to use Matplotlib and Seaborn libraries to create beautiful data visualization.
  • You will have an amazing portfolio of example python data analysis projects.
  • You will have an understanding of Machine Learning and SciKit Learn.
  • The course offers 100+ lectures and over 20 hours of information and more than 100 example python code notebooks.

Let’s check the below-mentioned courses for your career journey

3. Datacamp

Datacamp offers Data Analytics with Python course. It is one of the most well-known programming languages all across the world. You do not need prior coding experience to pursue the course.

Topics covered in this course

  • Introduction to Data Science in Python
  • Intermediate Python
  • Data manipulation with Pandas
  • Joining data with Pandas
  • Introduction to Statistics in Python
  • Introduction to Data Visualization with Seaborn
  • Data manipulation with Python
  • Importing & Cleaning Data with Python
  • Exploratory Data Analysis in Python
  • Sampling in Python
  • Hypothesis Testing in Python

Key benefits of the course

  • You will start from the basic to the most advanced level.
  • You will learn how to import, manipulate, and visualize data.
  • You can begin your data analyst training with interactive exercises.
  • You will get hands-on with Python libraries, including pandas, NumPy, Seaborn, etc.
  • You will learn why Python for data analysis is so popular.
  • You will get an opportunity to work with real-world datasets to grow your data manipulation.
  • You will also learn key statistics skills, like hypothesis testing.

Find out here the advanced courses for faster learning:

4. Swayam

Swayam offers another Data Analytics with Python. It is a 12-week course. The level of the course is undergraduate/postgraduate. After the completion of the course, you will get a certificate with logos of NPTEL and IIT Roorkee.

Topics covered in this course

  • Introduction to data analytics and Python fundamentals
  • Introduction to Probability
  • Sampling and sampling distributions
  • Hypothesis testing
  • Two sample testing and introduction to ANOVA
  • Two-way ANOVA and linear regression
  • Linear regression and multiple regression
  • Classification and Regression Trees (CART), and many more.

Also, read here the excellent and most-opted:

5. LearnDigital

LearnDigital offers another Data Analytics with Python course. It will teach you the fundamentals of the Python, which is necessary for data analysis. It will cover 4 modules.

Topics covered in this course

  • Set up Your Python Work Environment
  • Handle Fundamental Functions
  • Organize Objects and Programs within Project
  • Use Specialized Python Libraries

Key benefits of the course

  • You can set up your Python work environment.
  • You will use the fundamental functions and objects in Python.
  • You will organize objects with collections.
  • You will learn to manage program flow.
  • You can use Python libraries for data analysis.

6. IIT Madras

IIT Madras offers one of the best Data Analytics with Python courses. The learners will work Python libraries such as SciPy, NumPy, Matplotlib, etc. The students will learn Data Science with Python through real-world projects on industries like retail, and e-commerce.

Topics covered in this course

Module 1 – Linux and Python


  • Introduction to Python and IDEs
  • Python Basics
  • Object Oriented Programming
  • Hands-on Sessions and Assignments


  • Introduction to Linux
  • Linux Basics
  • Hands-on Sessions and Assignments for Practice

Module 2 – Data Analysis With MS-Excel

  • Excel Fundamentals
  • Excel For Data Analytics
  • Data Visualization with Excel
  • Excel Power Tools, and More

Module 3 – Data Wrangling with SQL

  • SQL Basics
  • Advanced SQL
  • Deep Dive into User-Defined Functions
  • SQL Optimization and Performance

Module 4 – GIT

  • Version Control
  • GIT

Module 5 – Advanced Statistics

  • Descriptive Statistics
  • Probability
  • Inferential Statistics

Module 6 – Python with Data Science

  • Extract Transform Load
  • Data Handling with NumPy
  • Data Manipulation Using Pandas
  • Data Preprocessing
  • Data Visualization
  • Introduction to Machine learning
  • Regression
  • Classification
  • Clustering
  • Supervised Learning
  • Unsupervised Learning
  • Performance Metrics

Module 7 – Deep Learning Using TensorFlow

  • Artificial Intelligence Basics
  • Neural Networks
  • Deep Learning

Module 8 – Natural Language Processing

  • Text Mining, Cleaning, and Pre-processing
  • Text classification, NLTK, sentiment analysis, etc
  • Sentence Structure, and Language Modeling
  • AI Chatbots and Recommendations Engine

Module 9 – Computer Vision

  • RBM and DBNs & Variational AutoEncoder
  • Object Detection using Convolutional Neural
  • Deploying Deep Learning Models and Beyond, and More

Module 10 – Deploying Machine Learning Models

  • Introduction to Machine Learning Models
  • Deploying Machine Learning Models

Module 11 – Visualization of data

  • Power BI Basics
  • DAX
  • Data Visualization with Analytics

Module 12 – Data Science Capstone Project

  • Extracting, and transforming data into intelligible data to gather insights for future betterment.
  • Data manipulation.
  • Analyzing the data for various problem statements.
  • Model selection, regression problems.
  • Checking the model using machine learning.

Module 13 – Data Science with Pyspark

  • Introduction to Big Data and Spark
  • RDDs
  • Advanced Concepts & Spark-Hive

Module 14 – Business Case Studies

  • Recommendation Engine
  • Rating Predictions
  • Census
  • Housing
  • Object Detection
  • Stock Market Analysis
  • Banking Problem
  • AI Chatbot

Key benefits of this course

  • It offers 50+ Live sessions across 7 months.
  • It offers 218 Hrs Self-paced Videos
  • The course offers 200 Hrs Projects& Exercises.
  • You will learn from experienced IIT Madras Faculty & Industry Practitioners.
  • You will get 1:1 learning with the guides.
  • You will get 3 Guaranteed Interviews by Intellipaat.
  • You can get 24*7 Support during the course.
  • You will get a certificate from CCE, IIT Madras after the completion of the course.

Must Check here the top-ranked:


7. Simplilearn

Simplilearn offers data analytics with Python courses for beginners as well as professionals. It is in collaboration with IBM. With the help of Python, you will know how to create data visualizations and apply statistics and predictive analytics in a business. They offer a master’s certificate program after completing the course.

They offer programming Basics and Data Analytics with Python. You will learn how to perform Data Analytics with Python using NumPy, manipulate in pandas, use SciPy, and learn machine learning using scikit-learn.

8. 360DigiTMG

360DigiTMG offers one of the best data analytics with Python courses. It offers various tools to learn the analytical process. It is in collaboration with IBM.

Course Modules and Program of Study

  • Python
  • Data Collection
  • Data Cleansing
  • Data Selection
  • Predictive Analysis
  • Machine Learning Program

Career Services & Placement Support

  • It collaborates with IBM and offers a certificate
  • It helps access to LMS for students for a lifetime
  • You will get practical experience in a live project
  • You can give an unlimited number of mock interviews
  • It offers blended learning – classroom and online learning
  • The course offers placement in well-known companies after the completion of the course
  • They apply Machine Learning approach to business decisions
  • It offers classroom and online sessions with the expert industry professionals

9. Imarticus Learning

Imarticus Learning is one of the best institutions that offer data analytics with Python courses. It is a Post Graduate course. It offers an excellent career through assignments, projects, etc.

Course Modules

  • Python
  • Machine Learning with Python

Career Services & Placement Support

  • The course offers profile enhancement by portfolio-worthy projects.
  • It builds the candidate’s resume.
  • It offers to access mock Q&As.
  • It offers expert guides so that the students can understand basics as well as practical learnings.
  • It also offers 100% placement support.

FAQs about Data Analytics with Python

1. Is Data Analytics using Python certification worth it?

Yes. Data Analytics with Python certification is worth it. It is the most well-known programming language that is used in big industries. This course is used for future betterment in business.

2. What built-in data types are used in Python?

These are as follows:

  • Number (int, float, and complex)
  • String (str)
  • Tuple (tuple)
  • Range (range)
  • List (list)
  • Set (set)
  • Dictionary (dict)

3. What are some of the most common libraries used in Python?

Those libraries are enumerated below:

  • Pandas
  • NumPy
  • SciPy
  • TensorFlow
  • SciKit
  • Seaborn
  • Matplotlib

4. How many types are there in data analytics?

There are four types of data analytics. Descriptive, Diagnostic, Predictive Analysis, Prescriptive Analysis.

5. What are the types of sampling processes used in data analysis?

They are five types:

  • Simple random sampling
  • Systematic sampling
  • Cluster sampling
  • Stratified sampling
  • Judgmental or purposive sampling

6. How much time does it take to understand Python programming language?

It takes generally two to six months to learn the basics of Python. But if you can grasp the language in a few minutes, it can take months or even years to master Python completely.

7. Do data analysts need to be good at math?

Prior knowledge is needed but that does not mean you should be an expert in maths to pursue the course.

8. Which is one of the best data analytics with Python courses?

Each course is worth it if you put your mind to it and want to make a thriving career out of the discipline. We have mentioned the top courses offered by the above-mentioned institutes. You can decide which one is best for you after dividing your needs and doing research.

9. Can a student of English major study Data Analytics with Python course?

Yes of course, why not! You can pursue Data Analytics with Python course even if you are from a non-technical background. But you should have a clear understanding of the course and course modules. You also have to know the basics of Python programming language.

Conclusion on Data Analytics with Python

Today big industries hire data analysts who know advanced Python programming language to fulfill their business goals. There can be a good chance to hire you if you have a degree in this field. You will get various opportunities after completing the course. The course will help you develop your technical skills as well as soft skills that you can use in your respected field. Data Analytics is a significant part of different sectors e.g., Government sectors, Corporate Sectors, Businesses, Health sectors, etc. We have discussed in detail the Top 9 Data Analytics with Python Courses for you that offer a certification program. Practical classes, classroom learnings, online classes, projects, assignments, LMS, etc. are offered by the institutes we have mentioned in this article. We wish you a prosperous journey in the near future after attending the course. We are sure of your success.

We wish you will have a great career ahead. Good Luck!

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