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Home >> Edegrees >> Data Science and Engineering E-Degree

Data Science and Engineering E-Degree

Build your career in Data Science using languages and tools like Python, Excel, R, Tableau, MySQL, PySpark and multiple hands-on projects.

5.0 Last Updated: 09/2020 Students Enrolled: 193 Instructors : ...
  • 9
  • 15
  • 470
  • 54
    Hrs Video
  • Exams
  • Certificate
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What it includes?
  • 30 day money back guarantee!
  • Lifetime Access. No Limits!
  • Certificate of Completion

Why This E-Degree

With this E-Degree, you will gain in-depth learning of all the comprehensive concepts of Data Science & Engineering in a step-by-step manner.

With this E-Degree, you’ll get:

  • 9 Comprehensive modules with a well-defined structure
  • Step-by-step interactive learning from scratch
  • Content curated from world-class instructors
  • Practical projects covering real-world issues
  • Hands-on training from industry experts
  • Exams & quizzes to measure your progress
  • Certificate upon completion of the E-Degree
  • Support for interview preparation
  • Expert-verified responses to ensure quality learning
  • E-books, guide books & code snippets
  • Lifetime access & update with no limits
  • 100% online & self-paced curation

What you’ll learn

With this E-Degree, you will explore the world of data science with structured modules having well-defined interactive content from world-class industry leaders. It will help you understand the science behind Data Science in a step-by-step manner.

Module 1: Data Scientist Tool Set - The Starter Tools

  • Learn how to import data into Excel from an Access database and CSV file and work with Data using VLOOKUP and Pivot tables in Excel.
  • Write complex SQL query to fetch data and solve the business problems with the help of SQL.
  • Complete understanding of foundational python.

Module 2: Advanced Tools for Data Scientists

  • Understand the most important concepts relating to the R programming language.
  • Understand key concepts like Regression and Decision Trees in R programming.

Module 3: Basic Data Visualization

  • Plot categorical, quantitative and mix of both type of data visualisations in Python.
  • Create data driven impressive insights using various kinds of plots with Titles, Labels, Legends etc and carry out quick exploratory data analysis using visuals in python using subplots, pair-plots etc.

Module 4: Statistics & Mathematics for Data Science

  • Get grasp on the most common statistical concepts applied in the field of data science and work through their application using Python coding and Google Colab notebooks.
  • Work with Confidence Intervals and Hypothesis Testing, Regression, Predictions, Classification Modelling as well as NLP.

Module 5: Machine Learning with Python

  • Understand the capabilities of machine learning (ML), and the knowledge to formulate your business problem to solve it effectively.
  • Build an army of powerful Machine Learning models and know how to combine them to solve any problem.
  • Master your Machine Learning fundamentals with algorithms and clustering using K-means.

Module 6: Business Intelligence

  • Ramp up your SQL skills by looking at advanced features of MySQL such as unions, views, triggers, stored procedures and more.

Module 7: Basic Data Analytics

  • Learn how to design databases to ensure data integrity. As a bonus, get a small introduction to NoSQL systems with MongoDB.
  • Work on Data Cleaning, Correlation Analysis, Time Series Analysis, Model Selection, Regression models and Decomposition in Business Intelligence in Data Science.

Module 8: Data Engineering Basics

  • Learn about the most common topics within the field of big data, you’ll have the vocabulary and skills needed to pursue applications in the field of Big Data.
  • Features and value of core Hadoop stack components including the MapReduce programming model.
  • Learn concepts of Data Mining and get introduced to the core techniques using practical exercises in Python, R and Rapid Miner.
  • Understand Data reduction, Data clustering, Anomaly detection, Association analysis, Regression analysis, Sequence mining and Text mining (Sentiment Analysis).

Module 9: Professional Data Engineering

  • Learn basic and advanced data visualization, dashboard and story development and integration of Tableau with Python and R.
  • Achieve scalable, high-throughput and fault-tolerant processing of data streams using PySpark.


This is an extensive designed program that will cater to all your Data Science needs. This complete E-Degree program includes 9 up-to-date modules, comprehensive courses, various labs and projects, quizzes and so much more to ensure complete learning in the most efficient way.

Module 1: Data Scientist Tool Set - The Starter Tools

Module 2: Advanced Tools for Data Scientists

Module 3: Basic Data Visualization

Module 4: Statistics & Mathematics for Data Science

Module 5: Machine Learning with Python

Module 6: Business Intelligence

Module 7: Basic Data Analytics

Module 8: Data Engineering Basics

Module 9: Professional Data Engineering

Why learn Data Science

The demand for data scientists has grown so unprecedented that Hiring Lab accepted that data science postings have rocketed to 256% - more than triple since 2013. But sadly, McKinsey said there was over 50% gap in the supply of data scientists versus demand. It was mainly due to the major skill gap which somehow is choking this positive technological change.

Let’s have a look on some exceptional statistics:

  • The US leads the data science market, requiring 190,000 data scientists by next year
  • The data science platform market size is expected to grow from $37.9 billion in 2019 to $ 140.9 billion by 2024
  • Every second 60,000 search queries are performed on Google and 1.2 trillion searches per year
  • 1 billion pieces of content are shared via Facebook’s Open Graph every day.
  • The U.S Bureau of statistics predicted an estimated 11.5 million new jobs in this field by 2026
  • Data Analytics Market is expected to grow at a CAGR of 30.08% from 2020 to 2023, which would equate to $77.6 billion
  • A 10% increase in data accessibility will result in more than $65 million additional net income for the typical Fortune 1000 company

Why learn with us

Eduonix is a pioneer in the technology-based knowledge industry delivering high-quality content across multiple areas of expertise. Our curriculum is prepared by a dedicated team of industry experts who bring in their years of experience for the professional training of learners.

Moreover, we have

  • 3 million+ learners
  • Global instructors
  • 30,000+ hours of high-quality content promising skill gain
  • Certificate upon completion
  • Job opportunities
  • Over a decade of experience in professional training
  • Up-to-date curriculum
  • 30-days money-back guarantee


Eduonix Learning Solutions

Statistics & Mathematics for Data Science

Eduonix creates and distributes high quality technology training content. Our team of industry professionals have been training manpower for more than a decade. We aim to teach technology the way it is used in industry and professional world. We have professional team of trainers for technologies ranging from Mobility, Web to Enterprise and Database and Server Administration.Eduonix creates and distributes high quality technology training content. Our team of industry professionals have been training manpower for more than a decade. We aim to teach technology the way it is used in industry and professional world. We have professional team of trainers for technologies ranging from Mobility, Web to Enterprise and Database and Server Administration.


India |MBA
Basic Data Visualization
I am a Machine Learning Data Scientist having more than 9 years of Industry experience in machine learning model building, Data Analytics, SAP and MIS reporting. I have worked in various domains including Industrial Products, Banking, General Insurance and FMCG. I am a professional who loves finding pragmatic solutions to real world problems. I am an engineering graduate with an MBA. I have done Machine Learning And Artificial Intelligence PostGraduate Program from Mc Combs University of Texas in Austin and Great Learnings. I have obtained Data Analyst Nanodegree Certification from Udacity. Also, I am a SAP Certified Associate. I have a passion for teaching and learning about new upcoming technologies. Some of the key skills that I have learned over the years are: Python, Machine Learning, Artificial Intelligence, CNN, LSTM, Natural Language Processing, Deep Learning, Recommendation System, Data Visualisation, Data Wrangling, Data Analysis, Data Analytics Statistics.

Aditya Dua

India |M.Tech
Professional Data Engineering

Aditya Dua is a Professional Application Developer, with extensive experience in building Workflow based applications which derive results based on data. In my Professional Role I have worked in varied capacities in various Fortune 500 companies. As an enterprise application developer I have worked in technologies from Java to J2EE including common frameworks like Spring, Hibernate. In my recent experience I am working as a Big Data Workflow developer in a Leading Bank in India working on Spark with Python.

John Ciolkosz

United States
Statistics & Mathematics for Data Science

John is a Mathematics Instructional Coach and a Data Scientist. He is employed by a secondary school district serving around 7,000 students annually in the role of the mathematics instructional coach. In addition to this role he also owns and operates C Solutions LLC, a consulting company specializing in data science, statistical analytics, and psychometric research. John's primary company work involves submissions of statistical and psychometric studies through ANSI (American National Standards Institute), and thus he can ensure all work carried out by himelf and C Solutions LLC meets the highest rigor of any standards set. 


Hong Kong
Data Scientist Tool Set - The Starter Tools
I've been a Linux systems admin for around ten years, I started in programming and with a great interest in scripting and dynamic websites and went on to manage systems for larger and small companies alike in the UK, China and Hong Kong. These days I consult on cloud computing in a wide range of settings, I transitioned to devops and infrastructure as code and am always trying to learn new technologies. I find that once you understand the foundations of something it can be transferred to something else so you're never truly starting from scratch, and I hope my videos help you to see the same!

Upendra Singhai

Data Engineering Basics

Upendra has been working in the software industry for over 17 years now. He has varied experience in various technologies with companies across the globe. These days his most of the time goes in pursuing his passion of teaching others about exciting technologies. 

He has spent a lot of time in enterprise solutions for Banking, Insurance and e-Governance. He specialises in emerging technologies. 


Machine Learning with Python

Chip Lambert

United States |Masters
Data Scientist Tool Set - The Starter Tools

Chip is an Associate Vice President Finance and Administration at Bluefield College. Chip Lambert has been developing websites and web applications for almost 20 years.  He is currently a software engineer for Jenzabar Inc. and an online instructor for Bluefield College, teaching courses in web and mobile application development.

Matthew Walz

United States
Machine Learning with Python

Matthew Walz is a Data Scientist and an Instructor at Binghamton University (SUNY) studying political science. He is interested in methodology with a focus on machine learning and artificial intelligence and their application in the social sciences for election forecasting. Currently Matthew is working as an instructor for PLSC 481M Election Forecasting at Binghamton University in addition to part-time work as a data scientist and conducting independent research. 


Business Intelligence

A Senior Data Scientist who leads AI/ML projects with more than 15 years of experience in ML, NLP, Automatic Speech Recognition, Image processing, OCR, AWS, Oracle, Big Data Spark Analytics, Data Science, Finance, Banking, Innovation, and Airlines domain. An AI/ML blogger who enjoy conducting ML/AI hackathon, imparting training, and writing research papers

Abhishek Agarwal

Advanced Tools for Data Scientists

Abhishek is a Data Science professional and worked with multiple MNCs for analytics projects. He has over 12 Years of experience in this field and specializes in Python, Tableau, QlikView, Statistics, Machine Learning, Risk Evaluation and Dashboarding.


An E-Degree is a collection of modules, projects and quizzes to make you proficient in the subject.
While an individual course contains only parts of a topic, an e-degree covers all important aspects of the topic covered. Similarly, a learning path will cover fewer topics than an e-degree.
  • A complete understanding of the concept
  • A certificate of completion
  • Lifetime access to the e-degree
  • Job opportunities
At the end of each section, you can submit your project URL by using CodePen, Github, Google Drive, etc.

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