Free Big Data Courses

The objective of this article is to describe about free Big Data courses available online.

About Big Data:

The business landscape keeps on widening so rapidly that traditional management, business and computing courses are not adequate enough to meet the requirement that will be arising out in near future in the business world. The traditional methods are of repetitive and rule-based in nature which by virtue of its being incapable of coping up with the newly emerging trend will be gradually replaced by Artificial Intelligence. In the knowledge era, the most value added job is going to be to manage knowledge, which includes how knowledge is created, mined, processed, shared and reused in different trades and industries. On the other hand, the amount of data and information getting generated day by day is becoming so huge and exponential that in another three years the size of the digital universe will reach 40 zettabytes from all sources including, websites, weblog, sensors, and social media. Therefore, needless to say, Big data is bound to play a vital role in bringing about a transformation into all spheres as to how we live, work and even think. These trends will have tremendous positive impact on how we look into the changing environment all around the globe and create policies.



 
In other words, Big data is a term used to represent large volume of data collected for analytical purpose which but for Big Data, can not be handled using the traditional data processing application software, as currently the pace at which the volume of data being generated in all sectors all over the world is too large and rapid to be contained within the traditional system. Big Data which can be characterized by 7Vs viz Volume, Velocity, Variety, Variability, Veracity, Visualisation and Value will, not only be accommodative to fulfil the present and future requirements but will also generate insights and value so that based on which an organisation can make better business decisions that will be useful in forming better business strategy and hence assured continual growth of the organisation.

Some of free Big Data courses available online are consolidated and furnished hereunder as a ready reckoner for the benefit of the viewers, from which one will be able to gather relevant information quickly on free online Big Data courses and make use of it.

1. Big Data Specialisation

This specialisation course is for those who evince keen interest in getting an overview of how big data is organised, analysed, and interpreted. This will create an avenue for gaining an understanding of what insights big data can provide through hands-on experience with the tools and systems used by big data scientists and engineers which, in turn, can be applied to solve real – world problems and questions and in taking better business decisions. Prior programming experience is not necessary. Your learning will be through the basics of using Hadoop with MapReduce, Spark, Pig and Hive. You can learn how one can perform predictive modelling and leverage graph analytics to model problems. You will be trained on asking the right questions about data, communicate effectively with data experts, and do the basic exploration of large, complex datasets. Finally, the skills acquired can be applied to do basic analyses of big data.



 
The following 6 courses are offered in Data Specialization.

Course 1: Introduction to Big Data

Duration:3 weeks of study @ 5-6 hours/week

Subtitles: English, Persian

About the Course: This course is designed for those who are new to data science and curious in knowing the necessity of Big Data Era coming into being. It is for those who have just given a thought over it in terms of making it useful in their business or career. As you are aware Hadoop has big data analysis easier and more accessible. Yes, this course gives basic knowledge on Hadoop and simplify your job.

This course also will help you gain knowledge of real world big data problems inclusive of the key sources of big data such as people, organizations, and sensors, describe 7 Vs, the architectural components and programming models used for scalable big data analysis.

Course 2: Big Data Modeling and Management Systems

Duration: 6 weeks of study @ 2-3 hours/week

Subtitles: English

About the Course: In this course, you will learn techniques using real-time and semi-structured data examples. Systems and tools discussed include AsterixDB, HP Vertica, Impala, Neo4j, Redis, SparkSQL. This course provides techniques to extract value from existing untapped data sources and discovering new data sources.

The importance of learning this course is that through this you will come to know how to differentiate between a traditional Database Management System and a Big Data Management System which is a basic requirement to understand why and how Big Data Analysis plays a vital role in the newly emerging scenario. Completion of Introduction to Big Data Course is recommended. Prior programming experience is not necessary but the ability to install applications and utilize a virtual machine is necessary to complete the hands-on assignments.



 

Course 3: Big Data Integration and Processing

Subtitles: English

About the Course: This will be useful in retrieving data from example database and big data management systems, In explaining the relationship between data management operations and the big data processing patterns which are essential for large-scale analytical applications, data integration and processing which on Hadoop and Spark platforms.

This course is for those new to data science. It is recommended to complete Introduction to Big Data prior to this. Prior programming experience is not required, but the skill to install applications and utilize a virtual machine is desirable to complete the hands-on assignments.

Course 4: Machine Learning With Big Data

Duration:5 Weeks, 3 – 5 hours per week

Subtitles: English

About the Course: Learning of this course will lead you to understand the volumes of data collected, to enable you to incorporate data-driven decisions into your process and to get an overview of machine learning techniques to explore, analyze, and leverage data and to create machine learning models and scale up the same to big data problems.



 

Course 5: Graph Analytics for Big Data

Duration: 4 Weeks @3-5 hours per week

Subtitles: English

About the Course: This course provides you a broad overview of the field of graph analytics through which new ways to model, store, retrieve analyze graph-structured data and interacting clusters within a graph can be learnt. It will throw light on how data network structure changes under different conditions and ultimately the techniques learnt can be applied to explore the importance of your data sets for your own projects. You will be introduced to the data set which will guide you through some exploratory analysis using tools such as Splunk and Open Office necessitating you to apply the more advanced tools you have learned including KNIME, Spark’s MLLib and Gephi. Finally, one will become well versed in bringing it all together to create engaging and compelling reports and slide presentations.

Course 6: Big Data – Capstone Project

Duration: 6 weeks

Subtitle: English

About the course: Learning this course will enable you to construct a Big Data Ecosystem. Using tools and methods learnt from the earlier courses, one will be able to analyze a data set simulating big data generated from a large number of users who are playing the imaginary game “Catch the Pink Flamingo”. You will also come across learning the typical big data science steps for acquiring, exploring, preparing, analyzing, and reporting. You will be introduced to the data set which will guide you through some exploratory analysis using tools such as Splunk and Open Office. Finally, you may be required to use the more advanced tools you have learned including KNIME, Spark’s MLLib and Gephi to move into more challenging big data problems and also you will acquire skills on how to bring it all together to create engaging and compelling reports and slide presentations.

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2. Cognitiveclass.ai

IBM is determined to tap the benefits of analysis, data science and potential learning from Big Data utilising the skills of the right people.

IBM has come forward to provide opportunities to learn the fundamental concepts required to develop, process and analyse big data. By doing so, IBM simplifies the process of participation in this sector and removes the traditional barrier and hurdles.

IBM conducts Cognitive Class which is an IBM community initiative to achieve this.This is aimed at providing training on-line freely including the content and access to tool sets used within the courses. Unlike other free online training sites, they wish to do it with a difference.

There are two important reasons why one has to participate in these courses.
1. One can get acquainted with groundbreaking technology free of cost.
2. IBM will gain the advantage of building confidence and contributing to the humanity with the fundamental skills which will make a difference.

At Cognitive Class, the participants will be awarded IBM recognized IBM Open Digital Badges that can be displayed in our LinkedIn profile, our site, other social media site and also in our email signature.IBM does not award degrees.

Through this website, you can learn the following subjects.

  • Big Data Analytics
  • Big Data Fundamentals
  • Big Data with IBM
  • Cognitive Analytics with IBM
  • Data Management with IBM
  • Data Science for Business
  • Data Science Fundamentals
  • Data Science with R
  • Deep Learning
  • Hadoop Administration
  • Hadoop Data Access
  • Hadoop Fundamentals
  • Hadoop Programming
  • Scala Programming for Data Science
  • Spark Fundamentals
  • Text Analytics
  • Watson Analytics

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3.Big Data: Data Visualisation

Data Visualisation is an important method for effective communication and analysing large data sheets. Hence learning data visualisation has become an integral part of big data course especially for drawing conclusions and decision making quickly and accurately. This course will throw light on understanding the basics on the methods, tools and processes involved in visualising big data.

This online course is offered free of cost by QUT through FutureLearn. QUT is an Australian University ranked in the top 2% of universities worldwide by the 2015 -16 Times Higher Education World University Rankings. Located in Brisbane, it attracts 47,000 students.

Duration of this free online course: 3 months @ 2 hours per week.

The topics that will be covered are Introduction to visualisation, Information visualisation, Scientific visualisation, Visualisation tools, Design approaches for visualisation and Visualisation for communication.

This is meant for those who want to learn how to produce visualisations that will be useful in better understanding of real-world big data problems. People equipped with knowledge in computer programming will benefit the most, however prior experience in using the relevant software is not a must.

At the end of the course, one will be able to explore big data frameworks, to demonstrate an integrated approach to big data and to effectively participate in a team working with big data experts.

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4. Processing Big Data with Hadoop in Azure HDInsight

Duration:5 Weeks @ 3-4 hours per week

Subtitle: English

About the course: This course tells you how to use the Hadoop technologies in Microsoft Azure HDInsight to build batch processing solutions that provide cleansed and reshaped data for analysis. You will be instructed to use technologies like Hive, Pig, Oozie, and Sqoop with Hadoop in HDInsight; and how to work with HDInsight clusters from Windows, Linux, and Mac OSX client computers. It is possible to complete the course and earn a certificate without completing the hands-on practices.

In this course, you’ll become conversant with the provision an HDInsight cluster, getting connectivity to an HDInsight cluster, to upload data, to run MapReduce jobs to use Hive to store and process data, to process data using Pig, to use custom Python user-defined functions from Hive and Pig,to define and run workflows for data processing using Oozie and finally to transfer data between HDInsight and databases using Sqoop.Knowledge on database concepts and basic SQL query syntax and programming fundamentals (for example, variable assignment, loops, conditional logic) are essential.

5. Managing Big Data with MySQL

About this course: Businesses are collecting more and more amounts of data with the hope that those will provide novel insights into how to improve businesses. By learning this course, you, the Analysts will become thorough with easy accessing this data and will have a strong competitive advantage in this data-smitten business world.

This course is meant for those who are interested in getting an introduction to the usage of relational databases in business analysis. One will be able to learn how relational databases work, and how to use entity-relationship diagrams to display the structure of the data held within them which in turn will help you understand how data needs to be collected in business contexts, and help you identify features you want to consider if you are involved in implementing new data collection efforts. You will also learn how to execute the most useful query and table aggregation statements for business analysts, and practice using them with real databases. Without awaiting someone else to provide you data from the company, you will be able to get the data by yourself.

6.Cloud Computing Applications, Part 2: Big Data and Applications in the Cloud

About this course: Cloud computing systems are built using a common set of core techniques, algorithms, and design philosophies, be it an open-source or used inside companies but all centred around distributed systems. Learning this course will create an avenue for you to learn about such fundamental distributed computing “concepts” for cloud computing.

Some of these concepts include Clouds, MapReduce, key-value/NoSQL stores, classical distributed algorithms, widely-used distributed algorithms, scalability, trending areas, etc.

Prior experience with C++ is required.

The course also emphasizes interviews with leading researchers and managers from both industry and academia.

This course is suitable for junior or senior undergraduates in computer science.This course will educate you basic algorithmic and design concepts for distributed systems, as used in today’s Cloud systems, most of which are conceptual and not programming oriented.

This course is not suitable for those: (1) aspiring to get a high-level overview of cloud computing; (2) planning to do detailed programming in a real cloud ; (3) who are not interested in getting along with theoretical and algorithmic concepts; (4) who expect to see industry-quality code in programming assignments (5) those who want to participate in lectures and videos and attempt quizzes in a hurry.

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7. Knowledge Management and Big Data in Business

Duration: 6 Weeks @ 6- 8 hours per week.

Subtitle: English.

Would you like to learn about the integrative power of knowledge management, Big Data and Cloud Computing, and how they impact the new business era ?. Then this the right course for you.

In this course, you will learn, The role of Knowledge Management (KM) practitioners in creating business value.

  1. The role of Knowledge Management (KM) practitioners in creating business value.
  2. To become familiar with the techniques and tools for capturing, processing, classifying and organizing knowledge.
  3. How to analyze large quantities of data and information through analytics.
  4. The role of social media and technologies in innovating new business services.
  5. To apply the principles you have learnt to company-based business projects.

The course is offered by the Knowledge Management and Innovation Research Center (KMIRC) of the Hong Kong Polytechnic University. This is suitable for participants with a background in humanities, management, social science, physical science or engineering. No prior technical background is needed.

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8. Big Data for Better Performance (BigData)

In this course, the techniques for predicting customer’s demand and preferences by using the data that is all around you can be learnt.This course shows you what ability big data has equipped with to create business opportunity. You can also see how smartly businesses use data to meet their business targets and get ahead of market trends.

The following video courses with quizzes are offered.

  1. Introduction to Big Data
  2. Big Data and Marketing
  3. Principles of Marketing with Big Data
  4. Big Data and Predictive Marketing

What will you learn?

  • To define big data and outline ways in which it is remapping the future of marketing
  • To identify the basic attributes of big data
  • To outline business challenges and opportunities in managing and using big data
  • To outline ways in which effective marketing can exploit big data
  • To provide examples of marketing strategies that can capture trackable data in order to improve the quality of attribution.

Duration: This course requires approximately 2 – 4 hours of study per week, but can vary depending on the student. This includes watching videos and taking quizzes and assessments. The total video time for this course is approximately 3 hours.




If you pass this course you’ll receive a Certificate of Achievement. While this certificate is not a formal qualification or credit, you can use it to demonstrate your interest in learning about this area to potential employers or educational institutions.

Conclusion:
Today Big Data represents around 10% of global IT markets but the way the trend progresses shows that within another four to five years, this will get enhanced to 33%. That will drive us to go in for launching new implementations which will lead us to further innovation and growth across all sectors and provide excellent opportunities for people working in Big Data environments and careers.

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