A Big Data Analytics and Machine Learning Course for Non-Computer Scientists

In this course, you will:

  • Learn about the emergence of big data, the expanding universe of dark data and the privacy issues that are created by the quantification of more and more aspects of our lives.

  • Discover how algorithms affect our world. Understand the workings of machine learning systems, especially neural networks and deep learning algorithms.

  • See the limitations of algorithms

  • Understand the principles and uses of smart systems including cyber-physical systems, smart platforms, and autonomous systems while recognizing the security issues involved in the deployment of this new technology.

  • Gain an understanding of the future outlook for the human-machine relationship

What you'll learn

In this engineering PDH course, we'll answer the following questions

  • Big Data Basics

    What is Big Data?

    What is Dark Data?

    Why is Big Data so important?

    How can Big Data help us to make decisions?

    Will Big Data Analytics replace human decision-making?

    What is the impact of Big Data on our privacy?

  • Algorithms

    How do algorithms impact our society today?

    What is machine learning and what are its applications?

    How do we train machines?

    What are neural networks and how do they work?

    What is deep learning and what is it used for?

  • Smart Systems

    What are smart systems and what are some of their applications?

    What is a smart platform?

    How do we address the security issues associated with smart networks?

  • The Human-Machine Relationship

    What are the risks associated with the presence of artificial intelligence in almost every aspect of our lives?

    How can these risks be mitigated?

    Will this technology ever completely replace human intelligence?


  • Duration : 4 hours

    This course allows participants to earn 4 engineering PDH (professional development hours).

  • Level: Introductory

    The course is non-technical in nature. It is an introductory course and thus all terms will be explained it should be accessible to anyone with a basic understanding of web technologies.

  • Audience

    Engineering, accounting, business and legal professionals • Anyone interested in learning the basics of big data analytics and machine learning and their applications

  • Requirements

    No prerequisites needed

  • Format: 100% online

    Start instantly and learn at your own schedule • On-demand video • 2-year access from mobile telephone and computer

  • Shareable Certificate: Yes

    Earn a shareable completion certificate indicating that you have earned 4 engineering PDH (Professional Development Hours).

How the Information Revolution Will Impact How We Live and Work

As Steve Lohr, of the New York Times, puts it

"Indeed the long view of the technology is that it will become a layer of data-driven artificial intelligence that resides on top of both the digital and the physical realms and today we're seeing the early steps toward that vision."

Although Steve Lohr's statement has a touch of science fiction to it, the surprising thing is that science fiction is becoming a new reality in our world.

Read more

The rise of big data and advanced analytics represents a profound change in both how we understand the world, make decisions and act on those decisions. In a recent paper by Ericsson, the authors capture some of the significance when they note,

“In contrast to digitalization, which enabled productivity improvements and efficiency gains on already-existing processes, datafication promises to completely redefine nearly every aspect of our existence as humans on this planet. Significantly beyond digitalization, this trend challenges the very foundations of our established methods of measurement and provides the opportunity to recreate societal frameworks, many of which have dictated human existence for over 250 years.”

Advanced data analytics can be interpreted as simply how we manage our world in an age of complex systems. It offers the possibility of actually seeing and understanding the complex systems that now run our world, from transport networks to social networks to cities and global supply chains. With complex data analytics, we actually have the possibility to manage these systems in a new way.

Sean Gourley founder of Quid states it clearly when he says,

"We live in a very complex world, there are 7 billion minds now, and those 7 billion minds have created a world that not one of them can understand and yet we still have to make decisions we have to decide whether or not to sent troops to Iraq and we have to decide what to do about climate change and we have to decide how to deal with a global financial market that doesn't want to stay still."

In this course, we will be looking at these four aspects of Big Data Analytics technology:

1. Data Analytics Basics

2. Big Data Fundamental Concepts

3. Advanced Algorithms

4. Smart Systems

Here's a summary of what we will be discussing.

Big Data Analytics

In the first section of this engineering PDH course, we give an overview of the domain of complex data analytics, touching upon many of the major themes that will be expanded upon during the rest of the course. Then, we are going to lay down a basic understanding of what we mean by the term analytics or data analytics. Finally, we will see that complex analytics enables us to answer complex questions.

Four Vs of Big Data

Big Data Fundamentals

In the second section, we will discuss the meaning and implications of Big Data. 

The term Big Data implies an increase in the quantity of data, but it also results in a qualitative transformation of how we store and analyze such data. We examine the details of this concept in this course.

We will see that the implicit premise of big data is that decisions can be made wholly based upon computerized models, shifting decision making from people to data and formal models. We learn about Dataism, the general underlying philosophy of big data, which holds that data is a primary source of truth, free of human bias or framing. We will give our viewpoint on whether or not this purist view is entirely true.

Finally, we will conclude this section of the course by presenting the fact that today, with the rise of information technology, we have gone from a world that was private by default, to a world that is public by default and, where, it takes extra effort to ensure privacy.

Advanced Algorithms

In the third section, we discuss the many ways algorithms have an increasingly material impact on society. From the rise of algorithms has come machine learning, a disruptive technology which used in a range of computing tasks where designing and programming explicit algorithms with good performance is difficult or not possible. 

Machine learning is a challenging area of computer science and engineering where many approaches to building intelligent systems exist. We will give an outline of 5 different approaches. We will dive deeper into the details of artificial neural networks which are computing systems inspired by the biological neural network of the brain. We will also present the workings of Deep Learning, a machine learning method based on neural networks. 

For better or worse our world is in the midst of a silent algorithmic revolution. Many of the decisions that humans once made are being handed over to mathematical formulas.  At the end of this section of the course, we talk about what algorithms can and can't do.

AI comparison

Smart Systems

In the final section of the course, we will discuss smart systems and how they incorporate the functions of sensing, actuation, and control in order to analyze a situation and make decisions.

We will see how the platform model will be important in developing smart solutions to almost all types of technologies in the coming decades.

We will learn of the inherent risk related to handing over an extraordinary amount of power to these automated algorithms. We conclude the course with a discussion of the future of the relationship between machines and human-machine relationship.

SOURCE:  Shutterstock


Video Lesson Sample


What engineers are saying about this course

I appreciate the sociological aspect of this course.

- AL of Quebec, Canada

For someone like me who has not ventured into this area of AI or Data Analytics, this course made it simple to understand and learn. It covered not only the basics, but also the significant results and consequences of where we are headed. Clear expressions from the narrator was not only easy to understand, but also easy to listen to. Thank you. Keep up the good work.

- FF of Ontario, Canada

Very informative and thought-provoking. Thanks!

- TG from Illinois, USA


Shareable Certificate

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Instantly download your certificate when you complete this course. It will state that you've earned 4 professional development hours (4 PDH). 

Share your course completion certificate directly from your student dashboard by:

1. Posting directly to social media:  Linkedin, Facebook and Twitter

2. Sharing its link

3. Downloading it as a PDF

Data Analytics and Machine Learning Course Certificate

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Enrollment Options

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Option 2:

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This course bundle includes two courses:
(1) Big Data and Machine Learning Explained (4h)
(2) The Blockchain: More than Cryptocurrency (4h)

Buy these courses together and save 25%. Complete both courses to earn 8 engineering PDH. Click below for details.
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Systems Thinking Expert

Joss Colchester

Joss has extensive experience within the domain of complex systems both within academic research (mathematical modelling of complex systems and network analysis) and practical systems engineering (designing and developing complex web-based information systems). He has a passion for taking abstract and complex concepts and making them concrete and accessible to as broad an audience as possible by combining clear graphics with well-structured course content.

Frequently Asked Questions

  • Are you an approved professional development course provider in Canada?

    Approval is not required. Canadian engineering boards do not approve, recommend or endorse any professional development course providers or courses.

  • Are you an approved professional development course provider in the USA?

    Approval is not required except in the following states: Florida, New York, New Jersey, North Carolina, Maryland, and Indiana.

    iPolytek has not yet sought to be approved in these states. Therefore, engineers from these state should not use our courses to accumulate professional development hours. If you are from one of these states and would like to take our courses in the future, let us know.

  • How long do I have to complete the course once I have purchased it?

    You have 2 years to complete this course. We will email you 30 days before your enrollment expires.

  • What is your refund policy?

    Due to the digital nature of our courses, we do not issue refunds. We encourage you to preview our courses and download the course notes for free before purchasing.


    The engineering boards of Florida, New York, New Jersey, North Carolina, Maryland, and Indiana require pre-approval of professional development course providers.

    iPolytek has not yet sought to be approved in these states. Therefore, engineers from these state cannot use our courses to accumulate professional development hours.

Professional Development

This course has been written to meet the professional development requirements defined by the orders of engineers of the following Canadian provinces and territories and the engineering boards of the following US states. These governing bodies do not require pre-approval of courses or course providers. For more information on the continuing education requirements set forth by your order or board, please click on your province or state below. 




AL, AK, AZ*, AR, CA*, CO*, CT*, DE, GA, HI*, ID, IL, IA, KS, KY, LA, ME, MA*, MI, MN, MS, MO, MT, NE, NV, NH, NM, ND, OH, OK, OR, PA, RI*, SC, SD, TN, TX, UT, VT, VA, WA*, WV, WI, WY

* These states do not have a professional development policy at this time.

It remains the engineer’s responsibility to determine whether an activity meets the guidelines set by their licensing body. It is also the engineer's responsibility to maintain and submit records of professional development activities to their engineering board.

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