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Data Scientist Training (76 Courses, 60+ Projects)

This Data Scientist Training Course includes 76 courses, 60 Projects with 632+ hours of video tutorials and Lifetime access.

You will also get verifiable certificates (unique certification number and your unique URL) when you complete each of them. This comprehensive course will teach you programming languages, machine learning, Hadoop, Business analytics, Data Visualization and other important analytics concepts.

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4.8 (6,785 ratings)

Python Data Scientist Courses (18 Courses)

Python Data Scientist Projects (6 Projects)

R Programming Data Scientist Courses (12 Courses)

R Programming Data Scientist Projects (11 Projects)

SAS Data Scientist Courses (9 Courses)

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What you get in this Data Scientist Training?

Online Classes

Technical Support

Mobile App Access

Case Studies

About Data Scientist Course

Course		No. of Hours
Machine Learning with SciKit-Learn in Python		8h 46m
Projects on ML - Predictive Modeling with Python		9h 44m
Matplotlib for Python Developers - Beginners		4h 24m
Matplotlib for Python Developers - Intermediate		2h 6m
Matplotlib for Python Developers - Advanced		6h 5m
Pandas with Python Tutorial		6h 05m
NumPy and Pandas		5h 07m
Project on Pandas - Data Management for Retail Dataset		4h 18m
Project on Python - Sentiment Analysis		1h 08m
Data Science with Python		4h 22m
Artificial Intelligence with Python		6h 36m
Video Analytics Using Opencv and Python Shells		2h 21m
Machine Learning using Python		3h 32m
Statistics for Data Science using Python		3h 56m
Project on Tensorflow - Implementing Linear Model with Python		1h 49m
Project - Data Analytics with Data Exploration Case Study		5h 19m
Project on ML - Random Forest Algorithm		1h 31m
Seaborn - Beginners		2h 34m
Seaborn - Intermediate		1h 22m
Seaborn - Advanced		1h 6m
PySpark - Beginners		2h 33m
PySpark - Intermediate		2h 16m
PySpark - Advanced		1h 21m
Machine Learning with Python Project - Predict Diabetes on Diagnostic Measures		1h 07m
R Studio UI and R Script Basics		4h 11m
R Programming for Data Science \| A Complete Courses to Learn		6h 22m
Project - Logistic Regression with R		4h 25m
Project - Decision Tree Modeling using R		1h 45m
Project on ML - Churn Prediction Model using R Studio		1h 25m
Financial Analytics in R - Beginners		3h 53m
Financial Analytics in R - Intermediate		1h 32m
Financial Analytics in R - Advanced		1h 4m
R for Finance - Beginners to Beyond		2h 18m
Comprehensive Course on R		4h 1m
Project on R - Forecasting using R		4h 47m
Project - Fraud Analytics using R & Microsoft Excel		2h 37m
Project - Marketing Analytics using R and Microsoft Excel		3h 32m
Machine Learning with R		20h 21m
Projects on R and Tableau - Customer Analytics		2h 11m
Projects on R and Tableau - Pricing Analytics		2h 02m
Business Analytics using R - Hands-on!		16h 14m
Project - Market Basket Analysis in R		39m
Project - Hypothesis Testing using R		3h 13m
Data Visualization with R Shiny - The Fundamentals		44m
Data Science with R		5h 8m
R Studio Anova Techniques Course		2h 18m
SAS Business Analytics for Beginners		10h 59m
Project on SAS - Predictive Modeling with SAS Enterprise Miner		9h 35m
Project on SAS - Quantitative Finance		3h 32m
SAS Statistics		8h 36m
SAS Output Delivery System(ODS)		9h 08m
SAS PROC SQL		14h 14m
SAS Macros Tutorials		7h 38m
Project on SAS - Advanced Analytics		12h 34m
Project on SAS - SAS Graph		2h 12m
Project on SAS - Programming using SAS DS2		5h 2m
SAS Advanced Project - SAS SQL		3h 03m
SAS Advanced Project - Macros		5h 12m
SAS Advanced Programming		11h 24m
Project on SAS - Categorical Data Analysis		7h 26m
Certified SAS Base Programmer		12h 48m
SAS Features for Starters		1h 54m
SAS PROC SQL Features		1h 53m
Big Data and Hadoop Training \| Online Hadoop Course		2h 5m
Hadoop Architecture and HDFS		6h 24m
MapReduce - Beginners		3h 39m
MapReduce - Advanced		5h 01m
Hive - Beginners		2h 55m
Hive - Advanced		5h 2m
PIG - Beginners		2h 15m
PIG - Advanced		2h 14m
NoSQL Fundamentals		2h 04m
Mahout		3h 55m
Apache Oozie		2h 18m
Apache Flume		20m
Apache Storm		2h 7m
Apache Avro		26m
Apache Spark - Beginners		1h 52m
Apache Spark - Advanced		5h 25m
Splunk Fundamentals		8h 44m
Splunk Advanced 01 - Knowledge Objects		9h 46m
Splunk Advanced 02 - Administration		37h 54m
Project on Hadoop - Sales Data Analysis		47m
Project on Hadoop - Tourism Survey Analysis		55m
Project on Hadoop - Faculty Data Management		35m
Project on Hadoop - E-Commerce Sales Analysis		36m
Project on Hadoop - Salary Analysis		49m
Project on Hadoop - Health Survey Analysis using HDFS		57m
Project on Hadoop - Traffic Violation Analysis		1h 28m
Project on Hadoop - Analyze Loan Dataset using PIG/MapReduce		2h 38m
Project on Hadoop - Case Study on Telecom Industry using HIVE		2h 4m
Project on Hadoop - Customers Complaints Analysis using HIVE/MapReduce		53m
Project on Hadoop - Social Media Analysis using HIVE/PIG/MapReduce/Sqoop		3h 37m
Project on Hadoop - Sensor Data Analysis using HIVE/PIG		4h 31m
Project on Hadoop - Youtube Data Analysis using PIG/MapReduce		3h 07m
Hadoop and HDFS Fundamentals on Cloudera		1h 26m
Project on Hadoop - Log Data Analysis		1h 33m
SPSS GUI and Applications		1h 16m
Project on SPSS - Correlation Techniques		2h 25m
Project on SPSS - Linear Regression Modeling		3h 16m
Project on SPSS - Multiple Regression Modeling		2h 35m
Project on SPSS - Logistic Regression		2h 04m
Project on SPSS - Multinomial Regression		2h 2m
SPSS GUI for Statistical Analysis		2h 08m
Tableau		5h 19m
Projects on BI Tools and Tableau Analytics		5h 48m
Business Intelligence with Tableau		5h 47m
Tableau Features Hands-on!		5h 47m
Project on Tableau - Super Store Business Requirements		46m
Analytics using Tableau		9h 03m
Statistical Analysis using Minitab - Beginners to Beyond		4h 29m
Minitab GUI and Descriptive Statistics		2h 48m
ANOVA in Minitab		53m
Correlation Techniques in Minitab		2h 21m
Project on Minitab - Regression Modeling		9h 54m
Minitab Predictive Modeling using Excel		56m
MATLAB - Beginners		2h 7m
MATLAB - Intermediate		47m
MATLAB - Advanced		4h 9m
Oracle SQL		18h 6m
Oracle PLSQL		12h 8m
Oracle DATABASE Admin DBA 1 Course		9h 4m
Machine Learning with Tensorflow		13h 2m
Hands-on Deep Learning Training		10h 9m
Project - Exploratory Data Analysis EDA using ggplot2, R and Linear Regression		2h 08m
Project on R - HR Attrition and Analytics		2h 52m
Project - Logistic Regression using SAS Stat		4h 33m
Project - Linear Regression in Python		2h 15m
Project on Python Data Science - Predicting the Survival of Passenger in Titanic		2h 11m
Project on R - Card Purchase Prediction		2h 31m
Project on Machine Learning - Develop Movie Recommendation Engine with Python		53m
Employee Attrition Prediction using Random Forest Technique and R		2h 2m
Project on Term Deposit Prediction using Logistic Regression CART Algorithm		1h 43m
Poisson Regression Project using SAS Stat		2h 24m
Machine Learning Project using Caret in R		1h 6m
Forecasting the Sales using Time Series Analysis in Python		2h 29m

Course Name	Online Data Scientist Course Bundle
Deal	You get access to all 76 courses, 60 Projects bundle. You do not need to purchase each course separately
Hours	632+ Video Hours
Core Coverage	This Data Scientist course will help you learn data science using R, Python, Machine Learning, Artificial Intelligence, Big data & Hadoop, Predictive Modeling, Business Analytics, Data Visualization and others.
Course Validity	Lifetime Access
Eligibility	Anyone serious about learning data science and wants to make a career in analytics
Pre-Requisites	Basic knowledge of data and analytics
What do you get?	Certificate of Completion for each of the 76 courses, 60 Projects
Certification Type	Course Completion Certificates
Verifiable Certificates?	Yes, you get verifiable certificates for each course with a unique link. These link can be included in your resume/Linkedin profile to showcase your enhanced skills
Type of Training	Video Course – Self Paced Learning
System Requirement	1 GB RAM or higher
Other Requirement	Speaker / Headphone

Online Data Scientist Course Curriculum

To make things easy for you, here’s a comprehensive Data scientist course. You need to invest significant hours to complete this all-in-all course, however, you going to reap its benefit later. Before we ever talk about data science the target audience, FAQs, let’s look at the data scientist training curriculum in detail –

Goals

The eventual goal of this course is to make one cognizant about Data science and all the approaches that are required to become a data science expert. leveraging unstructured data to extract some useful information will be the primary focus of all the modules and sub-module covered in this course.

Objectives

The soul objective of this course is very precise and clear. As the course is focused on Data science, our final objective will be to become ample proficient in this technology so that we can become able to work with data science to solve real organizational problems. To achieve this objective, we will be working on the secondary objective that is to master all the concepts that fall under the domain of data science.

Course Highlights

This course will help us master programming languages like Python and R. There are various modules based on Python training is available in this course where the trainees will be diving deep into these programming languages with the help of live examples and sample questions. SAS Data Scientist has also explained in the course keeping the hands-on practice in mind. In all the modules that refer to either any tool or technology that endorses data science, things have been detailed using precise examples. The course also includes Hadoop concepts where we will be learning about Hadoop from beginners’ perspective up to the advanced ones. The questions included in the Hadoop module will be explained by the educator in detail and in almost all of the scenarios the trainer will be using the real use cases to explain the topics.

Tableau will also be covered in this course. The trainees will learn how to leverage the presentation of data in the graphical form so that one can be able to extract the useful information out of the unstructured data. All the concepts regarding Minitab will also be covered in this course. To explain the working of Minitab, we have included some simple exercises that will help the trainees to understand how things work when we talk about working with Minitab. We will also be learning about Splunk in this training. You will get to learn how to leverage Splunk to work with data science. At last, the course will be explaining about Matlab. In the last module, we will be learning Matlab and will master all the features it offers.

Project Highlights

The course is comprised of modules and projects. In the module, we will cover the concepts that are used to implement data science while in the projects section, we will be working on real projects to make get practical exposure of how things work to provide a solution for any problem. In this course, we have included projects after every module so that the trainees can get a deep idea about all the concepts immediately after learning them. The course consists of projects on Python programming language where you will learn the advanced aspect of python or about the frameworks that are used to implement the features to leverage data science. For R programming languages, we do have separate projects. In the project based on R, you will get an in-depth idea of how to leverage these programming languages to draft solutions for the organizational level problems.

SAS Data Scientist Projects is one of the main project modules that is added to the course. Under this project, there are six sub-projects and it will take around forty-five hours to complete all these projects. Hadoop based projects have also included in the course where we will be working on six projects topics. It will help the trainees to become ample proficient in working with all aspects of big data. In addition to all of these, one will also be working on projects based on topics like Tableau, Minitab, Matlab, Splunk, and so on. After completing this course, the trainee will be able to implement all the features of Data science in production and will help the organization to get some useful information from the heap of raw data.

Certificate of Completion

What is Data Science?

Data science is a field where information comes from various sources, which in turn gets converted into valuable insights for business and IT strategies. The data collected from various sources can be structured, unstructured, or semi-structured. Massaging the data, formatting the data, analyzing the data, and extracting stories out of those data by dashboarding is a generic pipeline structure followed in the data science field.

This Data scientist course will take you through all these various tasks to well-versed you with every part of data science. While practicing Data science, you will come to know about various tools, algorithms, and Machine learning principles that are usually used.

Usually people mistaken data science with business intelligence. However, both are completely different. In other words, a higher level of business intelligence can be called data science.

Business intelligence usually deals with structured data, plotting its statistics, and visualization. However, data science deals with unstructured, structured, and semi-structured data. Data science is not just about statistics and visualization, it also includes predictions and various machine learning concepts.

Industry Growth Trend

The overall data science platform market is expected to grow from USD 19.58 billion in 2016 to USD 101.37 billion by 2021, at a CAGR of 38.9% from 2016 to 2021.
[Source - MarketsandMarkets]

Average Salary

Average Salary$120,301 per year

The average salary for a Data Scientist is $120,301 per year in the United States.
[Source - Indeed]

Which tangible skills you will learn in this data scientist course?

Today top-notch companies are relying on Data science skills be it through Python or some tools like SPSS etc. because of the exponential growth of data in the last decade. And hence they are in dire need of good Data science skills that can support data analysis and build highly reliable and efficient algorithms suitable for specific Organization needs. Below mentioned are some great capabilities and skills, that you will learn through this data scientist course.

Handling Dirty Datasets: Through this data scientist training course, you will learn various ways of handling dirty datasets (unstructured data). With a rise in the complexity of data and an increase in business demands, it becomes necessary to handle a wide variety of data like audio, video, etc. It’s not possible that one receives every time a structured data. Knowing data science skills to be it through R, Python, Minitab, SPSS, etc. will help you massage and reform varieties of data.

Programming skills: After taking this data scientist training, one will be able to explore, analyze datasets through programming languages like R, Python. Programming skills of these languages will help you target many custom requirements.

Story Telling: This data scientist training course will help you get the skills of storytelling. Data science skills finally end up when the insights extracted are well communicated until end users. Hence this data scientist course will tell you how to make a bigger impact on end-user along with great visualization.

Solve the business problem: This data scientist course will help you think and code in a way you can solve any business problem efficiently. Manipulating datasets, applying machine learning techniques can be ways of solving business problems.

Pre-requisites

Basics of Linear Algebra: Data Science deals with vectors, matrices, and its operations. If you don’t have a clear picture, it would be great if you can refresh it and then take this data scientist training. It will help you once you go deeper into data science-related algorithms.
Coding background: Learning languages like R, Python to explore datasets and analyzing it goes way easier if you have a programming background. It could be C, C++, Pearl anything. That way understanding logic from a programming perspective is helpful, and hence one can easily grab the Data science stuff.
Probability & Statistics: With a basic understanding of Probability & Statistics, this data scientist training course can be taken smoothly. This is because data science deals with many statistical tests and inferences, knowing probability and statistics will be a great boost.

Target Audience

Students of Analytics: If you’re a student of data science/analytics and want your career to drift deeper into that, this data scientist training is a sure shot solution for it. This data scientist course will make you build the gap between your college curriculum and industry related to Data science by giving you practical and live experiences of projects, which deal with data manipulation, data massaging, data visualization, storytelling.
Statistician & Model Developers: Data science deals with model generation and machine learning. If you want to fine-tune your knowledge over statistics and model generation, go ahead with this course. This data scientist training course will showcase lots of model generation use cases.
Professionals: If you are among auditors, solution recommenders, Project managers, or in a client-facing role etc., the Data scientist course will be an addon and help you excel more in your career. That’s because you will able to analyze and measure every bit of your task with analytics and data science. You can impress customers with data visualization and various facts extracted from their data.

Data Scientist Course FAQ’s

Why should I do this data scientist course?

This course is ideal and a great stepping stone for candidates who aspire to make their career in data science and its related tools like R, Python, Minitab, SPSS, Tableau, etc. I and the professionals who deal with data, be it structured, unstructured should take this data scientist course. Wherever data comes, data science has a key role to play there. Hence, taking this course will help you grow technically.

I don’t have a background in Data Science, can I do this data scientist course?

The answer is partial Yes and No. Full data science is based on probability and statistics. If you understand it well, the full data scientist training will be smoother, else you might get lost in between. It would be suggestible to clear basic of probability and statistics, and then do this course

Would this data scientist course help me in my career advancement?

Absolutely, without any doubt. Learn from this course about data science, get your hands dirty with your rigorous and repetitive practice, and this will create golden opportunities for you. Once you will start practicing, you will find yourself fascinated by data science and its related tools. This field is exciting, and this data scientist training course will make it even more exciting. There is ample of things to explore and learn about data science in this training.

Sample Preview

Career Benefits

It is a well-known fact, that dealing with varieties of datasets to bring the hidden insights, is in demand of today. All organizations today want to analyze their data so that they can make better decisions about their strategies. The person dealing with data and along with that critical thinking is something, the market is in dire need of.
In that scenario, knowing Data science skills, great thinking and communication to make the insights reach to the audience, is a great boon.
This data scientist training will help you kick start your career is a great way, by giving you lucid explanation about all perspective of Data Science.
Learning data science is an advantage for your better and competitive future. Growth in job and job security is certain if you have a good hold on data science.

Data Scientist Course Testimonials

Data science with python

The course goes through the different areas of data science with python. Besides a fundamental theory regarding the explained concepts, the diverse concepts are exemplified with short python programs. The lessons are good to understand and the programs presented to illustrate and implement the concepts are simple and significant.
Linked

Jorge Giro

Business Analytics using R

The data scientist course was very comprehensive and covered in detail the business analytics using R. The tutor used clear English and explained very carefully the different topics of the course. It is very rare to find a course online that covers that much information going from the basics of statistics to the application of R to business analytics. I think this is a competitive advantage of the course since the majority of this kind of courses available online are made for people who already know statistics or even some knowledge about the software itself, but this Data scientist course tried to cover them all which made very comfortable for me as a student.
Linked

Abderrahmane Friha

Amazing First Sashay with Customer Analytics

If you’re looking to dipping your toes into customer analytics, this Data scientist course is a good first start. It provides the foundation knowledge for customer analytics from mapping out the customer lifecycle and drilling down on what needs to be down per phase of the said lifecycle. I need to note that the data scientist training course explains from a bank / financial service standpoint, though this I feel allows the course to explain the concepts better instead of not having any examples at all.
Linked

Acee Vitangcol

Great content

Amazing material put together, it goes in-depth with functions on Excel, R, and SAS. I like the complexity and the level of knowledge especially the Excel area. If you are looking to analyze data regularly using excel 2010, or similar platforms such as R, this training is full of great content at a very high level.
Linked

Jorge Dominguez

Good Introduction to Marketing Analytics

It is a good Introduction to Marketing Analytics. It lists the typical activities carried out in the practice of predictive analytics. Furthermore, it helps to define how to make analytics more efficient, lists the type of models that are used in marketing and digital marketing, and some hints on the leading vendors of predictive analytics.
Linked

Ricardo Garibay-Martínez,

Excellent

It was a well-explained course! Easy to understand and practice. Recommended for beginners.
Linked

Arjun Gaggar

Statistics Using R

The data scientist training covers t-distribution, Z statistic, and Central limit theorem with exceptional clarity. It helped me in understanding the concepts with such a depth that I would never forget them now. The examples are highly practical and apt. The parallel execution of formulas in R makes it simple to remember rather than just going through the formulae, this Data Science course explains the underlying concepts first. It is the best course on R-Statistics I have come across so far.
Linked

Abbas Singapurwala

Business Analytics using R

Business Analytics is an excellent course for beginners in both Statistics and R programming. A lot of concepts have been covered from basics. It includes descriptive analysis, regression modeling, time series forecasting. It’s good knowledge if someone does not have any background in these techniques.
Linked

Ankit Tyagi

Very good

Detailed and informative course. covered everything in depth. need to know basic statistics for this Data scientist course. but this will lay a solid ground to become a data analyst. with this course realized how powerful is R software and its possibilities. Loved every bit of the data scientist training and would do more courses from EduCBA
Linked

Mudassir Ahmed

Data scientist training

After completing Business analytics on the R programming course, this was very advanced and helped me with my career towards becoming a data scientist. The data scientist training is well structured and the instructor is well organized. I would recommend this to all upcoming data scientists out there.
Linked

Thakgatso Jack Dikobo

Best Professional Development Platform

I have tried a lot of e-portals to have a complete set of curriculum on a specific professional course but did not find any. Thanks to EduCBA for their brilliant initiative to put details of the data scientist course and related topic in a single platform along issuing a course completion certificate……
Linked

SANJAY KUMAR KHILAR

Amazing

Very great content and easy to understand for beginners. A well structured informative course from an excellent instructor. The training starts from (1) a detailed introduction with real business examples, (2)the business analytics life cycle, (3)detailed understanding of R,(4)data manipulation and statistics, (5)great examples and understanding visualization, and many more. I would recommend this to anyone new or already pursuing their business analytics careers.
Linked

Thakgatso Jack Dikobo

Business Analytics using SAS

Great course. Very knowledgeable and covers a wide variety of topics. I would highly recommend this Data Science course to anyone trying to get started with SAS as a business analytics tool. Data validation and cleaning was very interesting. The section on data manipulation and data transformation covered a wide array of topics. One main topic covered was the date types and how they are assigned in SAS, which was a bit difficult to understand at first. Thank you for the opportunity.
Linked

Jonathan Johnson

New learning experience

I enjoyed the data scientist course and I believe the course has been a perfect way to be introduced to R programming and business analytics in general. The mix of statistics and R Programming goes to the core of the learning process. Great course very broad and helps generate further interest and awesome ideas. I am thinking of taking additional courses due to the many insights I gained from this Data Science course.
Linked

AJIBOLA ADETULA

Advanced SAS Programming

Great course for increasing your knowledge of SAS programming. Very knowledgeable and covers a wide variety of topics. I would highly recommend this course to anyone trying to increase their SAS Programming skills. The repeating of information as it related to each topic was a bit much for me but I’m sure it could be helpful for individuals that are first starting with the topic. This session covers MACROs in-depth; including MACRO Variable and MACRO processes. Overall the data scientist course was very informative and in-depth on all the topics it covered.
Linked

Jonathan Johnson

Basics of R Review

Good course, although bothered how the text in the slides is exactly what the tutor was saying, so there could be a text format of it also for copying. Maybe there should have been more lessons about the analysis part with R, to get an impression of what apx R can do with data. Overall, very useful, and will help me write my thesis!
Linked

Imola Fodor

Effective Tool for dashboard creation

This Data Science course is very informative and good for beginners. Clear, easy to understand and the instructor delivered the data scientist training in a very smooth way and covered a lot of topics. It lists the typical activities carried out in analytics and dashboard creation. Furthermore, it helps to define how to make a dashboard effectively. Simple and easily demonstrated Sales and Marketing analysis, chart, and table creation.
Linked

Patrick

Nice & Refreshing Course

This course on Hadoop and HDFS Basics was nice and refreshing. The instructor has explained all the concepts simply by providing sample examples. If you are completely new to Hadoop and need to learn basics then I recommend you to go for this Data Science course.
Linked

Almaamoon rasool abdali

Business Analytics Using R

This course is satisfactory for learning a few basics on R. I already have previous experience using R Studio, so there was not any new information for myself. But for someone who has no or very minimal experience with R, this Data Science course is good for teaching them the basics. People following these videos can download R and perform the same steps at the same time as the video.
Linked

Conner Capdau

Customer-Centric

This is a great data scientist training course that explains how customers relate directly with the different company departments and how each department relate to the vision of the company to satisfy the customers, I like the fact that the data scientist training its given with the assumption that the business it is moving towards the customer-centric vision, and how customer analytics will be the key to success.
Linked