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Data Science with Python Certification Course

Data Science with Python Certification Course
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Why enroll for Data Science with Python course?

pay scale by Edureka courseAccording to the U.S. Bureau of Labor Statistics, there will be around 11.5 million new jobs for Data Science professionals by 2026
IndustriesAvail upto Rs 14,500* from Government of India (GOI) incentives after successfully clearing the mandatory NASSCOM Assessment
Average Salary growth by Edureka courseThe national average salary of a data scientist is $119,563 per annum according to the U.S. Bureau of Labor Statistics

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Data Science with Python Certification Training Benefits

The number of Data Science jobs is expected to grow at a rate of 30% every year. Knowledge of Data Science coupled with Python programming skills opens up enormous opportunities for the Data Science job aspirants. This Data Science with Python course from Edureka will teach you the essential concepts from scratch and enable you to launch your dream career in this domain.
Annual Salary
Data Scientist average salary
Hiring Companies
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Annual Salary
Machine Learning Engineer average salary
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Data Analyst average salary
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Why Data Science with Python course from edureka!

Live Interactive Learning

Live Interactive Learning

  • World-Class Instructors
  • Expert-Led Mentoring Sessions
  • Instant doubt clearing
Lifetime Access

Lifetime Access

  • Course Access Never Expires
  • Free Access to Future Updates
  • Unlimited Access to Course Content
24x7 Support

24x7 Support

  • One-On-One Learning Assistance
  • Help Desk Support
  • Resolve Doubts in Real-time
Hands-On Project Based Learning

Hands-On Project Based Learning

  • Industry-Relevant Projects
  • Course Demo Dataset & Files
  • Quizzes & Assignments
Industry Recognised Certification

Industry Recognised Certification

  • Edureka Training Certificate
  • Graded Performance Certificate
  • Certificate of Completion

Data Science with Python Tools Covered

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  • HIVE -  tools

Data Science with Python Course Curriculum

Curriculum Designed by Experts
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Introduction to Python

10 Topics

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

Sequences and File Operations

7 Topics

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

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

13 Topics

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

Introduction to NumPy, Pandas and Matplotlib

13 Topics

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, colours, 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

Data Manipulation

6 Topics

Topics:

  • Basic Functionalities of a data object
  • Merging of Data objects
  • Concatenation of data objects
  • Types of Joins on data objects
  • Exploring a Dataset
  • Analysing 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

Introduction to Machine Learning with Python

6 Topics

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

Supervised Learning - I

6 Topics

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

Dimensionality Reduction

6 Topics

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

Supervised Learning - II

8 Topics

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

Unsupervised Learning

7 Topics

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

Association Rules Mining and Recommendation Systems

7 Topics

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

Reinforcement Learning

9 Topics

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

Time Series Analysis

10 Topics

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

Model Selection and Boosting

7 Topics

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

Statistical Foundations (Self-Paced)

8 Topics

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

Data Connection and Visualization in Tableau (Self-paced)

9 Topics

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

Advanced Visualizations (Self-paced)

10 Topics

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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Data Science with Python Course Description

Why Learn Python for Data Science?

Python has been one of the premier, flexible, and powerful open-source languages that is easy to learn, easy to use, and has powerful libraries for data manipulation and analysis. For over a decade, It has been used in scientific computing and highly quantitative domains such as finance, oil and gas, physics, and signal processing. It's continued to be a favourite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging programs is a breeze in Python with its built in debugger. It has evolved as the most preferred Language for Data Analytics and the increasing search trends also indicate that it is the Next Big Thing and a must for Professionals in the Data Analytics domain.

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

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 Sentimental analysis
  • Explain Time Series and its related concepts
  • Gain expertise to handle business in future, living the present

  • Edureka 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?

    Edureka’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 Training?

    The pre-requisites for Edureka's Python Data Science course training includes the fundamental understanding of Computer Programming Languages. Fundamentals of Data Analysis practiced over any of the data analysis tools like SAS/R will be a plus. However, you will be provided with complimentary “Python Statistics for Data Science” as a self-paced course once you enroll for the Data Science with Python certification course.

    Data Science with Python Certification Projects

     certification projects

    Industry: Automobile

    "MyCars" is a new age startup laying foundations in the setting up a car resell domain and they are setting up a team of ML experts to make predictive models to determine the pri....
     certification projects

    Industry: Consumer Complaint Resolution

    Predicting whether a complaint resolution will be accepted or rejected by a consumer can enable a business to proactively look at complaints which might be disputed and hence sav....

    Data Science with Python Certification

    You need to complete the modules successfully to earn a Joint Co-Branded Certificate of Participation by NASSCOM FutureSkills Prime and Edureka. On completing the course, the Learner is eligible for Government of India (GOI) incentives after successfully clearing the mandatory NASSCOM Assessment for which the learner will be awarded a NASSCOM certification. For more details please visit: https://futureskillsPrime.in/govt-of-India-incentives

    A skilling ecosystem focused on emerging technologies, powered by a partnership between the Ministry of Electronics and Information Technology, the Government of India, NASSCOM, and the IT industry. It seeks to propel India to become a global hub of talent in emerging technologies. FutureSkills Prime is one of the lighthouse schemes under the Government’s Trillion Dollar Digital Economy initiative. 
    • First of its kind government and industry partnership to drive a national skilling ecosystem for digital technologies. 
    • End-to-end skilling from assessment to certification. 
    • Affordable, credible content handpicked by industry leaders. 
    • Speed up learning with bite-sized course modules. 
    • Certifications recognized by the industry.
    GoI Incentive can be claimed by all Indian Nationals above 18 years of age. The current programme covers beneficiaries divided into the following broad categories: 

    • IT employees in IT Firms and Non-IT firms
    • Non-IT employees aspiring to use new and emerging technologies in their respective domains
    • Employees whose skills for a particular job have become outdated.
    • Central Govt. & State Govt. Employees including employees of PSUs & Autonomous bodies (Govt. Employees)
    • Fresh Recruits who are yet to take up a job, as well as undergoing/selected for internship & Apprenticeship roles in IT/ ITeS
    Mapping Your journey in 8 steps:
    • Enrolment in the Edureka portal
    • Successful completion of course modules
    • Quizzes, assignments, and certificate project submission
    • Assignment and project evaluation by Edureka 
    • Joint co-branded certificate of participation from NASSCOM and Edureka
    • Sign up on the FutureSkills Prime platform for mandatory FutureSkills Prime assessment
    • SSC Certificate issuance by Futureskills Prime on successful completion
    • Avail for GOI incentives upon successful completion of FutureSkills Prime assessment
    Yes, we offer a practice test in the Data Science with Python course to help you prepare for job interviews. 
    You do not need a coding background to enroll in this Data Science with Python course. The course begins with beginner modules in which we cover the fundamentals of Python coding. In fact, you do not need prior knowledge in Data Science and Machine Learning either. All relevant topics are a part of this course from scratch. 

    Right after the completion of this Data Science with Python course, you will obtain a certificate and will be eligible to apply for junior or associate data scientist jobs. After gaining some work experience, you can become a Senior Data Scientist or Machine Learning Engineer. This Edureka online course offers you the opportunity to connect with expert industry instructors to guide you through your desired career path.

    Please visit the page which will guide you through the top 100+ Data Science Interview Questions with answers.

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    Data Science with Python Course FAQs

    What is Data Science with Python?

    Data is all around us, and data science will help extract the information. Data science has many applications, and python can be used to implement them. Python is a generic language that can be used to build websites, backend APIs, and scripting. Python's built-in libraries, frameworks, and tools can be used to perform various operations in data science.

    Why should I learn Data Science with Python Course?

    Python is definitely one of the most popular languages in Data Science, which can be used for data analysis, manipulation, and visualization. It has access to many Data Science libraries, making it the perfect language for developing applications and implementing algorithms.

    Where Can I Learn Data Science with Python Course?

    Although there are many free learning resources available, finding one that teaches data science very well is recommended. You should choose a platform that will teach you interactively and has a curriculum designed to help you along your data science journey. Edureka is one such platform as we offer the best online python course for data science that will take you from beginner to data analyst in Python or data scientist.

    Can I learn a Python Data Science course online?

    Technology has made it easier and more efficient to learn online. It allows you to learn at your own pace without any barriers. Edureka's Data Science with Python certification course offers live classes and online access to study material from any location at any time. You will be able to grasp the key concepts quickly with our extensive and growing collection of tutorials, blogs, and YouTube videos. We offer a 24/7 support service to answer any questions you may have after your class ends.

    Who are the instructors for the Python Data Science Course?

    All the instructors at edureka! are practitioners from the Industry with minimum 10-12 yrs of relevant IT experience. They are subject matter experts and are trained by edureka for providing an awesome learning experience to the participants of Python Data Science Training.

    How long will it take for you to learn Python for Data science?

    It can take between five and 10 weeks to learn basic Python programming concepts, including object-oriented programming and basic Python syntax. It is important to note that the time it takes for Python programming depends on your experience with web development, data science, and other related fields.

    How will I execute practical’s in Edureka's Data Science with Python Certification Course?

    You will do your Assignments/Case Studies using Jupyter Notebook, already installed on your Cloud Lab environment, whose access details will be available on your LMS. You will be accessing your Cloud Lab environment from a browser. For any doubt, the 24*7 support team will promptly assist you.

    What if I have more queries with regards to Data Science using Python course?

    Just give us a CALL at +91 98702 76459/1844 230 6365 (US Tollfree Number) OR email at sales@edureka.co

    Why is it essential to learn Data Science with Python course?

    Python is preferred by data scientists over other languages because it has powerful machine learning libraries that can be used to build any machine learning algorithm. This allows for a better understanding of the current performance without sacrificing existing performance. These powerful frameworks allow data scientists to create the right neural networks. Python is the foundation of Google, YouTube and Instagram. It allows for multiple tasks to be automated and the use of these applications in various languages. The code is simple and well-documented. Many organizations are still not adopting a data-centric approach. The market lacks data literacy. To fill this gap in supply, you will need to study data science and its underlying areas by taking python data science training.

    What is CloudLab?

    CloudLab is a cloud-based Jupyter Notebook which is pre-installed with Python packages on the cloud-lab environment. It is offered by Edureka as a part of the Python Data Science Course where you can execute all the in-class demos and work on real-life projects in a fluent manner. You’ll be able to access the CloudLab via your browser which requires minimal hardware configuration. In case, you get stuck in any step, our support ninja team is ready to assist 24x7.

    Which kind of projects will be a part of this Data Science with Python Certification Course?

    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.

    Does Edureka provide any free learning resource for Data Science using Python course?

    If you are looking for free resources on Python and Data Science then read our blogs on Data Science tutorial, and Data Science Interview Questions.

    What if I miss a Data Science with Python Course class?

    You will never miss a lecture at edureka! 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.

    What type of job can I get after completing a Data Science Python course?

    This is an industry where opportunities are plenty, so once you have the education and qualifications, the jobs are waiting for you. To name a few, some of the most common job titles for data scientists include:

    • Business Intelligence Analyst
    • Data Mining Engineer
    • Data Architect
    • Data Scientist
    • Senior Data Scientist

    Will I get placement assistance after Data Science with Python Training?

    To help you in this endeavor, we have added a resume builder tool to your LMS. Now, you can create a winning resume in just 3 easy steps. You will have unlimited access to these templates across different roles and designations. All you need to do is, log in to your LMS and click on the "create your resume" option.

    Can I attend a demo session before enrollment?

    We have a limited number of participants in a live session of Data Science with Python course to maintain the Quality Standards. So, unfortunately, participation in a live class without enrollment is not possible. However, you can go through the sample class recording and it would give you a clear insight into how the classes are conducted, quality of instructors and the level of interaction in a class.

    Does Python help in Data Science?

    Python has several built-in libraries, frameworks, and tools that can be used to implement various functions of data science. Python's syntax is much more understandable than other programming languages like Scala and R. It is a data science tool that allows you to explore data science concepts in the most effective way possible. This makes it a highly skilled language and makes it the ideal choice for the Data Science Field.

    Is R better than Python for Data Science?

    TIOBE, Stack Overflow, and RedMonk indicate that Python is the most popular programming language in the broader tech community. This doesn't necessarily make it better, but it does suggest that it is more popular and has a stronger community for support and development.

    How is Python used in Data Science?

    Python has become the most demanding language in the data science communities due to it's compatibility and easy to use syntax. You can learn even if you don’t have an engineering and science background. Its versatility and easy to understand makes Python the most sought after-skills that big organizations are looking for in a data science professional.

    What will I get once I sign up for the Data Science with Python Course?

    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.

    Which companies will hire me once I become a Python for Data Science professional?

    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

    What are the popular cities where Edureka provides Data Science with Python courses?

    Here is the list of cities where Edureka provides Data Science with Python Course:

    What is the Avg Salary range for Data scientists in various countries?

    The salary range for Data scientists in various countries according to a salary survey by Payscale, Glassdoor, and talent.com:

    Countries

    Data scientists Avg Salary

    India

    ₹10,00,000 Per Year

    US

    $74439 Per Year

    Australia

    A$115,000 Per Year

    Canada

    C$79858 Per Year

    UK

    £52,052 Per Year

    Singapore

    S$70932 Per Year

    UAE

    AED 181776 Per Year


    What are the cost/training fee for the Data Science with Python Course in other countries?

    Find the cost of Data Science with Python Course in different countries:


    Countries

    Data Science with Python Course Cost

    India

    INR19,795

    US

    $539

    Australia

    $710

    Canada

    $701

    UK

    £413

    Singapore

    $737

    UAE

    $539

    What is the Average Salary of Data scientists across the world?

    According to Payscale, the average salary for a Data Scientist with Python skills is $98307.

    What are the other countries/cities where Edureka provides Data Science with Python courses apart from India and US?

    The countries/cities where Edureka provides Data Science with Python courses are:

    Can you become a Data Scientist with Python only?

    Although Python alone can be used to use data science in some instances, unfortunately for the corporate world, it's only part of the puzzle for companies to manage a large amount of data. Python is a fascinating coding language to master, especially for those who want to become data scientists. Its significance of it in data science should be considered and valued.
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