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Data Science with Python Certification

CertHippo Data Science with Python Certification Course is NASSCOM-accredited, meets industry requirements, and is authorized by the Government of India. This course will teach you crucial Python topics including data operations, file operations, and different Python libraries like Pandas, NumPy, and Matplotlib that are required for Data Science. This training is appropriate for both experts and novices. This Python for Data Science certification programmer will also teach you about Machine Learning, Recommendation Systems, and other Data Science ideas to help you get started in your Data Science career.

Why This Course

According to the US Bureau of Labor Statistics, there will be approximately 11.5 million additional Data Science positions by 2026.

After passing the required NASSCOM Assessment, you can claim rewards from the Government of India (GOI).

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According to the US Bureau of Labor Statistics, the nationwide average pay for a data analyst is $119,563 per year.

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Instructor-led live online classes

Data Science with Python Certification Course

Instructor-led DevOps live online Training (Weekday/ Weekend)

$799  $639

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Why Enroll In Course?

Data science career opportunities are expected to grow by 30% every year, and skill in Python programming and data science can open up a plethora of chances. The increased demand for qualified data scientists and machine learning engineers has driven more firms to adopt machine learning into their operations, allowing them to analyse and process data more quickly and effectively. Obtaining a Data Science and Machine Learning Certification from CertHippo is the best approach to land a lucrative job in this sector.

Training Features

Live Interactive Learning

  World-Class Instructors

  Expert-Led Mentoring Sessions

  Instant doubt clearing

Lifetime Access

  Course Access Never Expires

  Free Access to Future Updates

  Unlimited Access to Course Content

24x7 Support

  One-On-One Learning Assistance

  Help Desk Support

  Resolve Doubts in Real-time

Hands-On Project Based Learning

  Industry-Relevant Projects

  Course Demo Dataset & Files

  Quizzes & Assignments

Industry Recognized Certification

  CertHippo Training Certificate

  Graded Performance Certificate

  Certificate of Completion

Cloud Lab

  Preconfigured Lab Environment

  Infrastructure with Tools and Software

  Single Sign-On

About your AWS Course

AWS Solutions Architect Course Skills Covered

Managing Security

Designing Data Storage Solutions

Monitoring Cloud Solutions

Designing Resilient AWS Solutions

AWS Cloud Cost Optimization

Designing Identity Solutions

Course Curriculum

Topics:

  • Overview of Python

  • The Companies using Python

  • Different Applications where Python is Used

  • Discuss Python Scripts on UNIX/Windows

  • Values, Types, Variables

  • Operands and Expressions

  • Conditional Statements

  • Loops

  • Command Line Arguments

  • Writing to the Screen

 Hands-on:

  • Creating “Hello World” code

  • Variables

  • Demonstrating Conditional Statements

  • Demonstrating Loops

Skills You will Learn:

  • Basics of Python Programming

  • Command Line Parameters and Flow Control in Python

Topics:

  • Python files I/O Functions

  • Numbers

  • Strings and related operations

  • Tuples and related operations

  • Lists and related operations

  • Dictionaries and related operations

  • Sets and related operations

Hands-on:

  • Tuple - properties, related operations, compared with list

  • List - properties, related operations

  • Dictionary - properties, related operations

  • Set - properties, related operations

Skills You will Learn:

  • Taking input from the user and performing operations on it

  • Data types in Python

Topics:

  • Functions

  • Function Parameters

  • Global Variables

  • Variable Scope and Returning Values

  • Lambda Functions

  • Object Oriented Concepts

  • Standard Libraries

  • Modules Used in Python

  • The Import Statements

  • Module Search Path

  • Package Installation Ways

  • Errors and Exception Handling

  • Handling Multiple Exceptions

 Hands-on:

  • Functions - Syntax, Arguments, Keyword Arguments, Return Values

  • Lambda - Features, Syntax, Options, Compared with the Functions

  • Sorting - Sequences, Dictionaries, Limitations of Sorting

  • Errors and Exceptions - Types of Issues, Remediation

  • Packages and Module - Modules, Import Options, sys Path

Skills You will Learn:

  • Object Oriented Concepts

  • Python Functions, Standard Libraries and Modules

  • Handling Exceptions in Python

Topics:

  • Data Analysis

  • NumPy - arrays

  • Operations on arrays

  • Indexing slicing and iterating

  • Reading and writing arrays on files

  • Pandas - data structures & index operations

  • Reading and Writing data from Excel/CSV formats into Pandas

  • Metadata for imported Datasets

  • Matplotlib library

  • Grids, axes, plots

  • Markers, colors, fonts and styling

  • Types of plots - bar graphs, pie charts, histograms

  • Contour plots

 Hands-on:

  • NumPy library- Creating NumPy array, operations performed on NumPy array

  • Pandas library- Creating series and dataframes, Importing and exporting data

  • Matplotlib - Using Scatterplot, histogram, bar graph, pie chart to show information, Styling of Plot

 Skills You will Learn:

  • Basic Functionalities of the NumPy library in Python

  • Basic Functionalities of the Pandas library in Python

  • Basic Functionalities of the Matplotlib library in Python

Topics:

  • Basic Functionalities of a data object

  • Merging of Data objects

  • Concatenation of data objects

  • Types of Joins on data objects

  • Exploring a Dataset

  • Analyzing a dataset

Hands-on:

  • Pandas Function- Ndim(), axes(), values(), head(), tail(), sum(), std(), iteritems(), iterrows(), itertuples(), GroupBy operations, Aggregation, Concatenation, Merging and joining

 Skills You will Learn:

  • Performing data manipulation using various functionalities of the Pandas library in Python

Topics:

  • Python Revision (numpy, Pandas, scikit learn, matplotlib)

  • What is Machine Learning?

  • Machine Learning Use-Cases

  • Machine Learning Process Flow

  • Machine Learning Categories

  • Linear regression

Hands-on:

  • Linear Regression – Boston Dataset

 Skills You will Learn:

  • Machine Learning concepts

  • Machine Learning types

  • Linear Regression Implementation

Topics:

  • What is Classification and its use cases?

  • What is Decision Tree?

  • Algorithm for Decision Tree Induction

  • Creating a Perfect Decision Tree

  • Confusion Matrix

  • What is Random Forest?

 Hands-on:

  • Implementation of Logistic regression, Decision tree, Random forest

Skills You will Learn:

  • Supervised Learning concepts

  • Implementing different types of Supervised Learning algorithms

  • Evaluating model output

Topics:

  • Introduction to Dimensionality

  • Why Dimensionality Reduction

  • PCA

  • Factor Analysis

  • Scaling dimensional model

  • LDA

 Hands-on:

  • PCA

  • Scaling

Skills You will Learn:

  • Implementing Dimensionality Reduction Technique

Topics:

  • What is Naïve Bayes?

  • How Naïve Bayes works?

  • Implementing Naïve Bayes Classifier

  • What is a Support Vector Machine?

  • Illustrate how Support Vector Machine works?

  • Hyperparameter Optimization

  • Grid Search vs Random Search

  • Implementation of Support Vector Machine for Classification

 Hands on:

  • Implementation of Naïve Bayes, SVM

Skills:

  • Supervised Learning concepts

  • Implementing different types of Supervised Learning algorithms

  • Evaluating model output

Topics:

  • What is Clustering & its Use Cases?

  • What is K-means Clustering?

  • How K-means algorithm works?

  • How to do optimal clustering?

  • What is C-means Clustering?

  • What is Hierarchical Clustering?

  • How Hierarchical Clustering works?

Hands on:

  • Implementing K-means Clustering

  • Implementing Hierarchical Clustering

 Skills:

  • Unsupervised Learning

  • Implementation of Clustering – various types

Topics:

  • What are Association Rules?

  • Association Rule Parameters

  • Calculating Association Rule Parameters

  • Recommendation Engines

  • How Recommendation Engines work?

  • Collaborative Filtering

  • Content Based Filtering

Hands on:

  • Apriori Algorithm

  • Market Basket Analysis

Skills:

  • Data Mining using python

  • Recommender Systems using Python

Topics:

  • What is Reinforcement Learning?

  • Why Reinforcement Learning?

  • Elements of Reinforcement Learning

  • Exploration vs. Exploitation dilemma

  • Epsilon Greedy Algorithm

  • Markov Decision Process (MDP)

  • Q values and V values

  • Q – Learning

  • Values

 Hands on:

  • Calculating Reward

  • Discounted Reward

  • Calculating Optimal quantities

  • Implementing Q Learning

  • Setting up an Optimal Action

 Skills:

  • Implement Reinforcement Learning using Python

  • Developing Q Learning model in Python

Topics:

  • What is Time Series Analysis?

  • Importance of TSA

  • Components of TSA

  • White Noise

  • AR model

  • MA model

  • ARMA model

  • ARIMA model

  • Stationarity

  • ACF & PACF

 Hands on:

  • Checking Stationarity

  • Converting non-stationary data to stationary

  • Implementing Dickey-Fuller Test

  • Plot ACF and PACF

  • Generating the ARIMA plot

  • TSA Forecasting

 Skills:

  • TSA in Python

Topics:

  • What is Model Selection?

  • Need of Model Selection

  • Cross – Validation

  • What is Boosting?

  • How Boosting Algorithms work?

  • Types of Boosting Algorithms

  • Adaptive Boosting

Hands on:

  • Cross Validation

  • AdaBoost

 Skills:

  • Model Selection

  • Boosting algorithm using python

Topics:

  • What is Exploratory Data Analysis?

  • EDA Techniques

  • EDA Classification

  • Univariate Non-graphical EDA

  • Univariate Graphical EDA

  • Multivariate Non-graphical EDA

  • Multivariate Graphical EDA

  • Heat Maps

 Hands-on:

  • Implementing Graphical EDA Techniques

  • Implementing Non-Graphical EDA Techniques

Skills You will Learn:

  • Performing EDA on the dataset(s) in Python

Topics:

  • Data Visualization

  • Business Intelligence tools

  • VizQL Technology

  • Connect to data from File

  • Connect to data from Database

  • Basic Charts

  • Chart Operations

  • Combining Data

  • Calculations

Hands-on:

  • Connecting to data from File, Database, and Server

  • Performing operations on Hierarchies, Data Granularity and Highlighting feature

  • Creating calculated fields using basic functions

  • Defining LOD expressions

  • Creating Parameters

  • Performing User Input and What-if analysis

Skills You will Learn:

  • Data Distribution using various charts in Tableau

  • Combining Data using Joins, Unions and Data Blending

  • Sorting, Filtering and Grouping Techniques

  • Table Calculations in Tableau

Topics:

  • Trend lines

  • Reference lines

  • Forecasting

  • Clustering

  • Geographic Maps

  • Using charts effectively

  • Dashboards

  • Story Points

  • Visual best practices

  • Publish to Tableau Online

Hands-on:

  • Analyzing data using techniques including Forecasting, Trend Lines, Reference Lines, Clustering, and Geographic Maps

  • Building Dashboard Layout and Formatting

  • Building Story points

Skills You will Learn:

  • Advanced visualization techniques in Tableau

  • Building Dashboards and Stories in Tableau

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Certification

A skilling ecosystem fueled by a collaboration between the Ministry of Electronics and Information Technology, the Government of India, NASSCOM, and the IT sector. It aims to develop India into a global talent magnet for emerging technology. Future Skills Prime is one of the government's trillion-dollar Digital Economy initiative's lighthouse programmes.


To achieve a Joint Co-Branded Certificate of Completion from NASSCOM Future Skills Prime and CertHippo, you must successfully complete the modules. After successfully completing the course and passing the necessary NASSCOM Assessment, the learner is eligible for Government of India (GOI) incentives and will be issued a NASSCOM certification.


  • The first-of-its-kind collaboration between government and industry to build a nationwide skilling ecosystem for digital technologies. 
  • Complete skill development, from evaluation to certification. 
  • Content that is affordable and credible, vetted by industry leaders. 
  • Learn faster with bite-sized course units. 
  • Industry-recognized certifications

All Indian nationals over the age of 18 can apply for the GoI Incentive. The current plan includes beneficiaries from the following general categories:

  • IT workers in IT and non-IT organisations
  • Non-IT employees that want to leverage new and emerging technology in their fields
  • Employees whose talents for a specific job have become obsolete.
  • Employees of the Central and State Governments, as well as employees of PSUs and autonomous organisations (Govt. Employees)
  • Fresh Recruits who have not yet started working, as well as those undergoing/selected for internship and apprenticeship roles in IT/ITeS
  • Successful completion of course modules after enrollment on the Edureka portal
  • Quizzes, assignments, and the submission of a certificate project
  • Edureka assigned and evaluated projects Joint co-branded certificate of participation from NASSCOM and Edureka
  • Sign up for a FutureSkills Prime assessment on the FutureSkills Prime platform.
  • Futureskills Prime will issue an SSC certificate upon satisfactory completion.
  • Take advantage of GOI incentives after passing the Future Skills Prime assessment.

To obtain the CertHippo Data Science with Python Training course completion certificate, you must fulfil the following requirements:

  • Participate fully in this CertHipoo Data Science with Python Training Course.
  • Evaluation and completion of the mentioned quizzes and tasks.

Yes, Data Scientist is a viable career path for those who enjoy working with data and gaining insights from it. With the explosion of data in recent years, the demand for skilled data scientists has skyrocketed. As a Data Scientist, you can work in a range of areas, including healthcare, finance, and marketing. A strong foundation in statistics, machine learning, and programming skills, as well as a good understanding of business and domain expertise, are often required for the job. A Data Scientist is in charge of gathering, analysing, and interpreting massive and complicated data sets in order to guide company choices and strategies. Overall, data science is a tough and rewarding career path with a bright future.


Yes, Machine Learning Engineer is a viable career path for those who want to work with machine learning algorithms and put them into real-world applications. Machine learning is a fast expanding subject with a growing demand for people who can create and deploy machine learning models to automate tasks and extract insights from massive volumes of data. As a Machine Learning Engineer, you can work in a range of industries, including healthcare, banking, and e-commerce. A strong foundation in machine learning, programming abilities, and a decent understanding of software engineering principles are often required for the job. Overall, machine learning engineering can be a hard and rewarding professional path with a bright future.


To learn data science and machine learning as a novice, begin with Python programming and then on to data analysis. After mastering data analysis, one can move on to grasp the fundamentals of machine learning and apply machine learning algorithms to real-world issues. CertHippo Data Science with Python Certification Training is an organised learning experience that assists novices in gaining practical experience and developing the abilities required to become effective in data science and machine learning.


Data Science with Python Certification teaches data science, machine learning, and Python programming. This certification is useful for a number of reasons:

  • Mastery of Key Skills: Certification demonstrates that a person has a good understanding of data science ideas, machine learning methodologies, and Python programming skills.
  • Improves Job Prospects: Data science and machine learning are fast-growing businesses, and certification can help you get a better job by demonstrating your skills in these fields.
  • Increases Earning Potential: Certified data scientists and machine learning engineers frequently earn better pay than non-certified colleagues.
  • Enhances Credibility: Certification is a recognized mark of knowledge that can boost a person's credibility in their area.
  • Maintains Skills: Data science and machine learning are topics that are always growing, and certification demands employees to stay up to date with the latest technology and methodologies.
  • Enables Career Advancement: Certification allows individuals to develop their careers by proving mastery of important skills and enhancing their value to their organization.

This Data Science with Python course does not require any prior coding knowledge. The course begins with core modules that cover the principles of Python coding. In fact, no prior expertise of data science or machine learning is required. This course includes all necessary topics from the ground up.


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Online Training FAQs

Data is all around us, and data science will help us extract it. Python may be used to implement numerous data science applications. Python is a general-purpose programming language that may be used to create websites, backend APIs, and scripting. Python's built-in libraries, frameworks, and tools may be used to execute a variety of data science activities.

Python is unquestionably one of the most popular data science languages, capable of data analysis, manipulation, and visualization. It offers access to a large number of Data Science libraries, making it ideal for designing applications and applying algorithms.

Although there are many free learning materials accessible, it is essential that you choose one that teaches data science extremely effectively. You should select a platform that will teach you interactively and includes a curriculum that will guide you through your data science journey. CertHippo is one such platform, as we provide the best online Data Science with Python course for data science, taking you from novice to data analyst or data scientist in Python.

Online learning has become easier and more efficient as a result of technological advancements. It allows you to learn at your own speed with no restrictions. CertHippo Data Science with Python certification course includes live courses as well as online access to study materials from any place and at any time. With our wide and expanding library of lessons, articles, and YouTube videos, you will be able to comprehend the important ideas fast. We provide a 24-hour support service to address any queries you may have after your class has concluded.

CertHippo! instructors are all industry practitioners with at least 10-12 years of relevant IT experience. These are subject matter experts who have been educated by CertHippo to provide an excellent learning experience to Python Data Science Training attendees.

Learning basic Python programming principles, such as object-oriented programming and basic Python syntax, might take between five and ten weeks in a Data Science with Python Course. It is crucial to remember that the amount of time it takes to learn Python programming is dependent on your previous expertise in web development, data science, and other relevant topics.

You will complete your Assignments/Case Studies using Jupyter Notebook, which is already installed on your Cloud Lab environment and whose login information is available on your LMS. You will be using a browser to access your Cloud Lab environment. If you have any questions, the 24 hour support crew will respond quickly.

You can give us a CALL at +1 302 956 2015 (US) OR email at info@certhippo.com

A Data Science Expert analyzes and interprets big and complicated datasets using statistical, mathematical, and computational tools to extract insights, make predictions, and guide decision-making. They are proficient in programming languages like as Python or R, and they manage, process, and analyze data using a variety of tools and technologies such as machine learning methods, data visualization, and database systems. They may work in a variety of fields such as banking, healthcare, marketing, and so forth.

Data scientists flavor Python over other languages because it includes powerful machine learning libraries that can be used to create any machine learning method. This gives for a better knowledge of present performance without jeopardizing it. These sophisticated frameworks enable data scientists to build the appropriate neural networks. Python is at the heart of Google, YouTube, and Instagram. It enables the automation of many operations as well as the usage of these apps in a variety of languages. The code is straightforward and well-documented. Several firms have yet to implement a data-centric strategy. The market is lacking in data literacy. You will need to learn data science and its underlying fields by taking python data science training to meet this supply deficit

Cloud Lab is a Jupiter Notebook that is hosted in the cloud and comes pre-installed with Python packages. CertHippo offers it as part of the Python for Data Science Course, where you can perform all in-class demos and work on real-life projects fluently. You'll be able to use your browser to access the Cloud Lab, which requires very no hardware equipment. If you get stuck at any point, our support ninja team is available 24 hours a day, 7 days a week.

A Data Science Expert should have a combination of technical and non-technical skills, including:

  • Strong programming skills in languages like Python, R, and SQL.

  • Proficiency in statistical analysis, machine learning, and data visualization techniques.

  • Knowledge of data structures, algorithms, and database systems.

  • Strong problem-solving skills and ability to work with large and complex datasets.

  • Understanding of business processes and ability to communicate effectively with stakeholders.

  • Knowledge of software engineering principles for building scalable and maintainable data pipelines.

  • Continual learning mindset to keep up with the latest trends and technologies in the field.

Project Title: Consumer Complaint Resolution 

Problem Statement: Predicting which complaints have a higher potential to be disputed and identifying systematic issues can help enhance the quality of communication and satisfactory resolution.

You will never miss a lecture at Certhippo! You can choose either of the two options:

  • View the recorded session of the class available in your LMS.

  • You can attend the missed session in any other live batch.

This is an area with a lot of chances, so if you have the education and qualifications, the employment will come to you. Some of the most prevalent job titles for data scientists include, to mention a few:

  • Business Intelligence Analyst

  • Data Mining Engineer

  • Data Architect

  • Data Scientist

  • Senior Data Scientist

We have introduced a resume creation feature to your LMS to assist you in this attempt. You may now design a winning CV in just three simple steps. You will have unrestricted access to these templates in all roles and designations. All you have to do is sign in to your LMS and select the "make your resume" option.

To maintain the Quality Standards, we have a restricted number of participants in a live session of the Data Science with Python course. Participation in a live class without enrolment is thus not feasible. But, you may listen to a sample class recording to get a good idea of how the lessons are run, the quality of the teachers, and the degree of engagement in a class.

Python has a number of modules, frameworks, and tools that may be used to accomplish various data science functions. Python syntax is far more intelligible than those of other computer languages such as Scala and R. It is a data science tool that enables you to investigate data science ideas in the most efficient manner possible. As a result, it is a highly skilled language and an excellent choice for the Data Science Industry.

According to TIOBE, Stack Overflow, and RedMonk, Python is the most popular programming language in the larger IT world. This does not necessarily imply that it is better, but it does imply that it is more popular and has a larger community for support and growth.

Python has become the most popular language among data scientists due to its interoperability and simple syntax. Even if you don't have a background in engineering or science, you can learn. Python's versatility and ease of use make it one of the most sought-after abilities that large firms want in a data science practitioner.

You can access all the Specialization courses when you sign up for the course. Once you have completed the work, you will receive a certificate added to your Accomplishments page. From there, you can print it or add it to LinkedIn. You can view and read the course content for free if you don't want to pay.

Data science has grown by a substantial extent today. Companies in almost every industry are trying to have a data science team to help them use their data for the company’s progress.

Here, we have compiled a list of reputed companies that are currently hiring data scientists. 

1. Sigmoid

2. Mindtree

3. LinkedIn

4. Paypal

5. Oracle

6. TCS

7. ZIGRAM

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Course Description

Why Learn Data Science with Python?

Python is a premier, flexible, and strong open-source language that is simple to learn and use, with extensive modules for data processing and analysis. It has been used in scientific computing and highly quantitative sectors such as finance, oil and gas, physics, and signal processing for over a decade. It has remained a popular choice among data scientists who use it to construct and run Machine Learning applications and other scientific calculations. Python's concise syntax and quick compilation feature decreased development time in half. Python's built-in debugger makes debugging applications a snap.It has emerged as the most popular Language for Data Analytics, and rising search patterns show that it is the Next Big Thing and a requirement for Data Analytics Professionals.

What are the objectives of our Data Science with Python Training Course?

After completing this Data Science using Python Certification course, you will be able to:

  • Programmatically download and analyze data

  • Learn techniques to deal with different types of data – ordinal, categorical, encoding

  • Learn data visualization

  • Using I python notebooks, master the art of presenting step by step data analysis

  • Gain insight into the 'Roles' played by a Machine Learning Engineer

  • Describe Machine Learning

  • Work with real-time data

  • Learn tools and techniques for predictive modeling

  • Discuss Machine Learning algorithms and their implementation

  • Validate Machine Learning algorithms

  • Perform Text Mining and Sentiment analysis

  • Explain Time Series and its related concepts

  • Gain expertise to handle business in future, living the present

CertHippo offers the best online course for Python Data Science. Enroll now with our data Science with Python training and get a chance to learn from industrial giants.

Who should go for this Python Data Science online course?

Certhippo’s course is a good fit for the below professionals:

  • Programmers, Developers, Technical Leads, Architects

  • Developers aspiring to be a ‘Machine Learning Engineer'

  • Analytics Managers who are leading a team of analysts

  • Business Analysts who want to understand Machine

  • Learning (ML) Techniques

  • Information Architects who want to gain expertise in

  • Predictive Analytics

  • Professionals who want to design automatic predictive models

What are the prerequisites for this Data Science with Python Course?

The fundamental grasp of Computer Programming Languages is required for the CertHippo Python Data Science course study. Foundations of Data Analysis performed using data analysis programmers such as SAS/R will be advantageous. Nevertheless, you will be supplied with gratis "Python Statistics for Data Science" as a self-paced course after you enroll for the Data Science with Python certification course.

What is Data Science with Python syllabus?

The Data Science with Python Course syllabus covers:

  • Introduction to Python

  • Sequences and File Operations

  • Deep Dive – Functions, OOPs, Modules, Errors and Exceptions

  • Introduction to NumPy, Pandas and Matplotlib

  • Data Manipulation

  • Introduction to Machine Learning with Python

  • Supervised Learning - I

  • Dimensionality Reduction

  • Supervised Learning - II

  • Unsupervised Learning

  • Association Rules Mining and Recommendation Systems

  • Reinforcement Learning

  • Time Series Analysis

  • Model Selection and Boosting

  • Statistical Foundations (Self-Paced)

  • Data Connection and Visualization in Tableau (Self-paced)

  • Advanced Visualizations (Self-paced)

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Selenium Certification

A skilling ecosystem fueled by a collaboration between the Ministry of Electronics and Information Technology, the Government of India, NASSCOM, and the IT sector. It aims to develop India into a global talent magnet for emerging technology. Future Skills Prime is one of the government's trillion-dollar Digital Economy initiative's lighthouse programmes.


To achieve a Joint Co-Branded Certificate of Completion from NASSCOM Future Skills Prime and CertHippo, you must successfully complete the modules. After successfully completing the course and passing the necessary NASSCOM Assessment, the learner is eligible for Government of India (GOI) incentives and will be issued a NASSCOM certification.


  • The first-of-its-kind collaboration between government and industry to build a nationwide skilling ecosystem for digital technologies. 
  • Complete skill development, from evaluation to certification. 
  • Content that is affordable and credible, vetted by industry leaders. 
  • Learn faster with bite-sized course units. 
  • Industry-recognized certifications

All Indian nationals over the age of 18 can apply for the GoI Incentive. The current plan includes beneficiaries from the following general categories:

  • IT workers in IT and non-IT organisations
  • Non-IT employees that want to leverage new and emerging technology in their fields
  • Employees whose talents for a specific job have become obsolete.
  • Employees of the Central and State Governments, as well as employees of PSUs and autonomous organisations (Govt. Employees)
  • Fresh Recruits who have not yet started working, as well as those undergoing/selected for internship and apprenticeship roles in IT/ITeS
  • Successful completion of course modules after enrollment on the Edureka portal
  • Quizzes, assignments, and the submission of a certificate project
  • Edureka assigned and evaluated projects Joint co-branded certificate of participation from NASSCOM and Edureka
  • Sign up for a FutureSkills Prime assessment on the FutureSkills Prime platform.
  • Futureskills Prime will issue an SSC certificate upon satisfactory completion.
  • Take advantage of GOI incentives after passing the Future Skills Prime assessment.

To obtain the CertHippo Data Science with Python Training course completion certificate, you must fulfil the following requirements:

  • Participate fully in this CertHipoo Data Science with Python Training Course.
  • Evaluation and completion of the mentioned quizzes and tasks.

Yes, Data Scientist is a viable career path for those who enjoy working with data and gaining insights from it. With the explosion of data in recent years, the demand for skilled data scientists has skyrocketed. As a Data Scientist, you can work in a range of areas, including healthcare, finance, and marketing. A strong foundation in statistics, machine learning, and programming skills, as well as a good understanding of business and domain expertise, are often required for the job. A Data Scientist is in charge of gathering, analysing, and interpreting massive and complicated data sets in order to guide company choices and strategies. Overall, data science is a tough and rewarding career path with a bright future.


Yes, Machine Learning Engineer is a viable career path for those who want to work with machine learning algorithms and put them into real-world applications. Machine learning is a fast expanding subject with a growing demand for people who can create and deploy machine learning models to automate tasks and extract insights from massive volumes of data. As a Machine Learning Engineer, you can work in a range of industries, including healthcare, banking, and e-commerce. A strong foundation in machine learning, programming abilities, and a decent understanding of software engineering principles are often required for the job. Overall, machine learning engineering can be a hard and rewarding professional path with a bright future.


To learn data science and machine learning as a novice, begin with Python programming and then on to data analysis. After mastering data analysis, one can move on to grasp the fundamentals of machine learning and apply machine learning algorithms to real-world issues. CertHippo Data Science with Python Certification Training is an organised learning experience that assists novices in gaining practical experience and developing the abilities required to become effective in data science and machine learning.


Data Science with Python Certification teaches data science, machine learning, and Python programming. This certification is useful for a number of reasons:

  • Mastery of Key Skills: Certification demonstrates that a person has a good understanding of data science ideas, machine learning methodologies, and Python programming skills.
  • Improves Job Prospects: Data science and machine learning are fast-growing businesses, and certification can help you get a better job by demonstrating your skills in these fields.
  • Increases Earning Potential: Certified data scientists and machine learning engineers frequently earn better pay than non-certified colleagues.
  • Enhances Credibility: Certification is a recognized mark of knowledge that can boost a person's credibility in their area.
  • Maintains Skills: Data science and machine learning are topics that are always growing, and certification demands employees to stay up to date with the latest technology and methodologies.
  • Enables Career Advancement: Certification allows individuals to develop their careers by proving mastery of important skills and enhancing their value to their organization.

This Data Science with Python course does not require any prior coding knowledge. The course begins with core modules that cover the principles of Python coding. In fact, no prior expertise of data science or machine learning is required. This course includes all necessary topics from the ground up.


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