Learn from Home Offer

Learn from Home Offer
This All in One Data Science Course Bundle is an Ultimate bundle of 400+ courses with 1500+ hours of video tutorials and Lifetime access.
This is not all, you also get verifiable certificates (unique certification number and your unique URL) when you complete these courses. It covers core such as - Artificial Intelligence, Machine Learning, Business Intelligence, Data Visualization, Deep Learning, Big data and Hadoop, Internet of Things (IoT), Cloud Computing, SalesForce, Statistical Analysis.
Machine Learning Course
Data Science with Python Course
Data Scientist Course
Deep Learning Course
IoT Course
Bundle | No. of Courses | No. of Projects | Hours | Actual Price |
---|---|---|---|---|
Data Science with Python Training (24 Courses, 14+ Projects) | 24 | 14 | 110+ | |
Machine Learning Training (20 Courses, 29+ Projects) | 19 | 29 | 178+ | |
SPSS Training Program (5 Courses, 9+ Projects) | 5 | 9 | 30+ | |
Hadoop Training Program (20 Courses, 14+ Projects, 4 Quizzes) | 20 | 14 | 135+ | |
Azure Training (6 Courses, 5 Projects, 4 Quizzes) | 6 | 5 | 67+ | |
Microsoft Power BI Training (6 Courses, 4 Projects) | 6 | 4 | 45+ | |
Informatica Training (7 Courses) | 7 | - | 47+ | |
Data Scientist Training (85 Courses, 67+ Projects) | 85 | 67 | 660+ | |
Tableau Training (8 Courses, 8+ Projects) | 8 | 8 | 55+ | |
AWS Training (10 Courses, 5 Projects, 4 Quizzes) | 10 | 5 | 80+ | |
EViews Econometrics Training (6 Courses, 5+ Projects) | 6 | 5 | 25+ | |
MS SQL Training (16 Courses, 11+ Projects) | 16 | 11 | 70+ | |
Artificial Intelligence AI Training (5 Courses, 2 Project) | 5 | 2 | 45+ | |
Splunk Training Program (4 Courses, 7+ Projects) | 4 | 7 | 56+ | |
R Programming Training (13 Courses, 20+ Projects) | 13 | 20 | 120+ | |
Cloud Computing Training (18 Courses, 5+ Projects) | 18 | 5 | 102+ | |
MATLAB Training (3 Courses, 1 Project) | 3 | 1 | 8+ | |
Minitab Training (8 Courses, 3 Projects) | 8 | 3 | 40+ | |
IoT Training (5 Courses, 2+ Projects) | 5 | 2 | 44+ | |
Deep Learning Training (18 Courses, 24+ Projects) | 18 | 24 | 145+ | |
Apache Pig Training (2 Courses, 4+ Projects) | 2 | 4 | 18+ | |
Pandas and NumPy Tutorial (4 Courses, 5 Projects) | 4 | 5 | 37+ | |
Hive Training (2 Courses, 5+ Projects) | 2 | 5 | 25+ | |
SEO Training (12 Courses, 6 Projects) | 12 | 6 | 66+ | |
Multisim Training (3 Courses, 2+ Projects) | 3 | 2 | 6+ | |
Predictive Modeling Training (2 Courses, 15+ Projects) | 2 | 15 | 79+ | |
Google Analytics Training (12 Courses, 2+ Projects) | 12 | 2 | 54+ | |
Salesforce Training (2 Courses, 2+ Projects) | 2 | 2 | 25+ | |
MatPlotLib Tutorials (3 Courses, 2 Project) | 3 | 2 | 16+ | |
PySpark Tutorials (3 Courses) | 3 | - | 6+ | |
MapReduce Training (2 Courses, 4+ Projects) | 2 | 4 | 19+ | |
Seaborn Tutorial (3 Courses, 2+ Projects) | 3 | 2 | 8+ | |
TensorFlow Training (11 Courses, 3+ Projects) | 11 | 3 | 55+ | |
Statistical Analysis Training (15 Courses, 10+ Projects) | 15 | 10 | 140+ | |
SAS Training (9 Courses, 10+ Projects) | 9 | 10 | 123+ | |
Sqoop Course (2 Courses, 2 Projects) | 2 | 2 | 9+ | |
Business Analytics Training (14 Courses, 8+ Projects) | 14 | 8 | 88+ | |
Data Visualization Training (15 Courses, 5+ Projects) | 15 | 5 | 105+ | |
Business Intelligence Training (12 Courses, 6+ Projects) | 12 | 6 | 121+ | |
Octave Training (3 Courses, 1+ Projects) | 3 | 1 | 13+ | |
Forecasting Models Course (4 Courses, 14 Projects) | 4 | 14 | 54+ | |
Time Series Course (4 Courses, 7 Projects) | 4 | 7 | 64+ | |
Ansible Training (1 Course, 4 Projects) | 1 | 4 | 8+ | |
Fraud Analytics Course (1 Course, 2 Projects) | 1 | 2 | 7+ | |
Talend Data Integration Training | 2 | 4 | 5+ | |
QlikView Training (2 Courses, 1 Project) | 2 | 1 | 9+ | |
OpenCV Training (1 Course, 4 Projects) | 1 | 4 | 12+ | |
Docker Training (4 Courses, 3 Projects) | 4 | 3 | 11+ | |
AWS Solutions Architect Training (2 Courses) | 2 | - | 15+ | |
AWS Sysops Administrator Training (1 Courses) | 1 | - | 8+ | |
DevOps Training (7 Courses, 1 Project) | 7 | 1 | 20+ | |
Apache Spark Training (3 Courses) | 3 | - | 13+ | |
Apache Storm Training (1 Courses) | 1 | - | 2+ | |
Mahout Training (1 Courses) | 1 | - | 3+ | |
SSIS Training (2 Courses) | 2 | - | 7+ | |
Customer Analytics Training (2 Courses) | 2 | - | 3+ | |
Marketing Analytics Training (4 Courses, 2 Projects) | 4 | 2 | 10+ | |
CloverETL Tutorial (2 Courses) | 2 | - | 4+ | |
Keras Training (2 Courses, 8 Projects) | 2 | 8 | 24+ | |
Cassandra Training (12 Courses, 2 Projects) | 12 | 2 | 37+ | |
Apache Solr Training (1 Course) | 1 | - | 3+ | |
Time Series Analysis and Forecasting with Python (7 Courses, 9 Projects) | 7 | 9 | 62+ | |
Time Series Analysis and Forecasting with Minitab (2 Courses, 4 Projects) | 2 | 4 | 23+ | |
Time Series Analysis and Forecasting with Tableau (3 Courses, 6 Projects) | 3 | 6 | 30+ | |
Kubernetes Training (2 Course, 2 Projects) | 2 | 2 | 10+ | |
Time Series Analysis and Forecasting with R (3 Courses, 16 Projects) | 3 | 16 | 66+ | |
Scikit-learn Course (3 Courses, 1 Project) | 3 | 1 | 30+ | |
Time Series Analysis and Forecasting with Excel (11 Courses, 8 Projects) | 11 | 8 | 67+ | |
Time Series Analysis and Forecasting with SAS (2 Courses, 7 Projects) | 2 | 7 | 62+ | |
SQLite Tutorial (3 Courses, 1 Project) | 3 | 1 | 11+ | |
Chef Software Training (1 Course) | 1 | - | 2+ | |
NLP tutorial using Python NLTK (2 Courses, 2 Projects) | 2 | 2 | 14+ | |
Kibana Training (1 Course, 3 Project) | 1 | 3 | 14+ | |
CouchDB Course (1 Course) | 1 | - | 4+ | |
Apache Kafka Training (1 Course, 1 Project) | 1 | 1 | 7+ | |
Data Modeling Course (10 Courses, 5 Projects) | 10 | 5 | 107+ | |
Predictive Modeling with Python Course (2 Courses, 6 Projects) | 2 | 6 | 22+ | |
Predictive Analytics Course (4 Courses, 5+ Projects) | 4 | 5 | 54+ | |
Predictive Modeling with SAS Enterprise Miner (5 Courses, 1+ Projects) | 5 | 1 | 9+ | |
Bonus Data Science Courses | 32 | - | 100+ | FREE |
Total | 360+ | 458+ | 1500+ |
The below table of courses gives you the complete overview of all the courses, its links, description and the number of hours required to complete each Data Science course–
Big Data and Hadoop training, Hadoop architecture, HDFS, MapReduce Fundamentals, MapReduce advanced, HIVE fundamentals, Hive Advanced, PIG Fundamentals, PIG Advanced.
Amazon Web Services, AWS Certified Solution Architect, Amazon Cloud Computing, Technical essentials, simple email services, certified DevOps, SysOps, Cloud migration, business users.
SAS – An introduction, GRAPH, DS2 programming, STAT, ODS, PROC SQL, Advanced PROC SQL, SAS SQL, 10 more course.
Machine Learning Statistics essentials, learning with Tensor Flow, five projects in Machine Learning, Artificial Intelligence with Python, 11 more courses.
Comprehensive Course on R, Business Intelligence using R, Machine Learning with R, Fraud Analytics, Customer Analytics, Marketing Analytics, Pricing Analytics.
SEO Secrets of Page Optimization, CRO Beginners, Advanced, Google Analytics, Display Advertising, Email Marketing etc.
IoT automation with ESP8266, Pythion for IoT tutorials, advanced python, Raspberry Pi.
Application to predictive Modeling, Analysis of Variance ANOVA, correlation techniques, regression and predictive modeling.
Descriptive statistics, correlation techniques, linear regression modelling, logistic regression, multinomial regression, analyze data for statistical analysis.
Business Intelligence with Tableau, Customer Analytics using R and Tableau, Pricing Analytics.
Virtualization and Cloud Computing, AWS, Microsoft Azure, Azure essentials, EC2, Azure Data Lake, AWS technical essentials.
Microsoft Azure, Data Lake, Data Factory, Azure PAAS, developing your applications on Azure, Migration of websites to Azure, migrating .NET based web applications.
Salesforce administration beginner lessons, complete guide to Salesforce, Visual Force.
Application to Econometrics Modeling, Descriptive statistics, regression modelling, correlation techniques, multivariate modeling, VAR modeling, 3 more courses.
Splunk Fundamentals, Splunk advanced knowledge objects and administartion.
Informatica beginners, advanced, Informatica, DAC training, Teradata, ETL tools, Informatica Powercenter.
Microsoft SQL fundamentals, transact sql, table creation, SQL Server Indexes, Views, Stored procedures, triggers, T-SQL beginners and advanced, SSIS.
Data Science with Python, AI, Video Analytics, Pandas, Machine Learning, Statistics using Python.
Data Science with Python, AI, Business Intelligence and Machine Learning using R, SAS, Hadoop, Hive, tableau analytics, MATLAB, Predictive modelling, Eviews, Pricing and Customer Analytics.
Statistical tools in Microsoft excel, Machine Learning, Statistics, SAS, Business Analytics, Predictive Modelling, Eview, Splunk fundamentals.
SAS Business Analytics, SAS Beginners, Fraud Analytics, Customer Analytics, Financial Analytics, Customer Analytics, Marketing Analytics.
BI-Business Intelligence, Business Intelligence using Microsoft Excel, Business Intelligence with Tableau, BIP-Business Intelligence Publisher using Siebel, Customer Analytics using R and Tableau, Pricing Analytics using R and Tableau, Analytics using Tableau, Predictive Modeling using Minitab, Predictive Modeling using SPSS.
Data Analytics with QlikView, Artificial Intelligence and Machine Learning Training Course, Machine Learning using Python, Machine Learning - Statistics Essentials, Business Intelligence with Tableau, Customer Analytics using R and Tableau, Pricing Analytics using R and Tableau, EViews - Econometrics Modeling, Clover ETL Data Integration & Others
Data Science is a field of computer science that includes several technological and mathematical subjects to efficiently develop several data science applications or tools in the area of computer science including several concepts such as artificial intelligence, neural network, Statistics, and machine learning programming techniques. This area of Data Science also provides Machine Learning Algorithm techniques, Tableau tools usage and applications, data Mining & modeling, Data Visualization using Tableau tool. The usage of different other tools like NumPy, Seaborn, Pandas, Matplotlib, and TensorFlow are explained well.
This Data Science subject has a wide range of technical concepts such as Python, R Programming, AWS (Amazon Web Services), several AWS certifications, Data Science tools and advanced techniques to handle large amounts of data to perform bulk operations. There are also different statistical techniques in this area such as regression techniques, multi regression techniques, logistical and polynomial techniques.
Yes, Any Python Developer or Big Data Engineer or Hadoop or AWS Developer or prospective Technical Data Science Engineer or Developer who is willing to learn the latest technologies in Data Science concepts and Big Data basics are can choose this Data Science course which is very worth.
YES, this All in One Data Science course is a better choice for your profession to choose from. This course can be learned easily and does not require any pre-requisites of computer or data science basics. Anyone who is very interested and keen on learning the latest data science tools and frameworks can choose this Data Science course.
Yes. this course provides good and added value to your profession or career and profile in terms of the data science or big data core concepts and AWS or Hadoop Development to the career or profession along with verifiable certifications from Edu CBA Academy which gives greater benefits in obtaining further roles in career.
Yes, this is a good course to learn any latest data science-related technology or to prepare for any job interview or any professional certification. Any knowledge of python or data science related programming language or big data or Hadoop development is recommended which is an added benefit upon learning the contents of this course. This All in One Data Science course needs a minimum of 1500+ hours to complete.
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
The 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 Science course tried to cover them all which made very comfortable for me as a student.
Linked
If you’re looking to dipping your toes into customer analytics, this Data Science 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 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
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
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
It was a well-explained course! Easy to understand and practice. Recommended for beginners.
Linked
The course 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
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
Detailed and informative course. covered everything in depth. need to know basic statistics for this Data Science 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 course and would do more courses from EduCBA
Linked
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 course is well structured and the instructor is well organized. I would recommend this to all upcoming data scientists out there.
Linked
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 course and related topic in a single platform along issuing a course completion certificate……
Linked
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
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
I enjoyed the 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
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 course was very informative and in-depth on all the topics it covered.
Linked
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
This Data Science course is very informative and good for beginners. Clear, easy to understand and the instructor delivered the course 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
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
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
This is a great course that explains how customers relate directly with the different company departments and how each department relates to the vision of the company to satisfy the customers, I like the fact that the course it is 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
By signing up, you agree to our Terms of Use and Privacy Policy.
By signing up, you agree to our Terms of Use and Privacy Policy.
Courses | No. of Hours | |
---|---|---|
Microsoft Excel 2010 - DAX in Power Pivot | 0h 11m | |
Financial Modeling - Automobile Sector | 4h 27m | |
Equity Research Report Writing - Dos and Don'ts | 1h 9m | |
Financial Modeling - Indian Telecommunication Sector | 3h 48m | |
Android Mobile Apps Foundation Course | 5h 17m | |
Financial Ratio Analysis - A Case Study on Asian Paints | 1h 15m | |
Financial Modeling - Broadcasting Sector | 2h 5m | |
Java Servlets Tutorial | Java Servlets Courses | 9h 26m | |
Medical Diagnostics Market in India | 0h | |
Financial modeling - ACC | 1h 58m | |
DDM - An Overview to Dividend Discount Model (DDM) | 0h 36m | |
Private Equity (PE) Excel Modeling | 2h 25m | |
Financial Modeling - Time Warner | 3h 48m | |
Microsoft Excel 2013 Dashboard Course | 2h 23m | |
Financial Modeling - Automobile Sector | 4h 27m | |
Excel 101 - Basic Excel for 2013 and Later Versions | 4h 1m | |
Statistical Tools in Microsoft Excel | 1h 11m | |
Financial Functions In Excel - Microsoft Excel 2013 Course | 2h 36m | |
Advanced Charts Features in Microsoft Excel 2010 | 0h 8m | |
Microsoft Excel - Worksheet Dialog Box Controls and Form Controls | 0h 27m |
This website or its third-party tools use cookies, which are necessary to its functioning and required to achieve the purposes illustrated in the cookie policy. By closing this banner, scrolling this page, clicking a link or continuing to browse otherwise, you agree to our Privacy Policy