Fundamentals of Machine Learning

In this workshop you will learn the fundamental concepts of Machine Learning and what it is. Machine Learning has been a hot topic in recent years especially in the field of medicine, finance, and the auto industry. It is used from recommending what kind of movies you would like to watch to Google’s driverless cars. Machine Learning is the future and there is high demand for people that have the skills to use it.

The course will cover:

  • Harness the power of R to build common machine learning algorithms with real-world data science applications
  • Get to grips with R techniques to clean and prepare your data for analysis, and visualise your results
  • Discover the different types of machine learning models and learn which is best to meet your data needs and solve your analysis problems
  • Predict values by using R to build decision trees, rules, and support vector machines
  • Forecast numeric values with linear regression, and model your data with neural networks
  • Evaluate and improve the performance of machine learning models
  • Learn specialised machine learning techniques for predictive modeling and classification and more

Day 1

Intro to Machine Learning and R (2 hr)

  • List
  • Vectors
  • Data frame
  • Struct
  • Summary functions
  • Simple calculations

Morning Tea (15min)

Support Vector machine (3hrs)

  • 1 hr theory
  • 2 hr practical

Lunch (30min)

Using linear regression to forecast medical expenses (2 hrs)

  • 1 hr theory
  • 2 hr practical

Who attended the workshops:

This course is recommended for:

  • Data Analysts
  • Data Scientists
  • Statisticians
  • Researchers and Scientists in Universities and Institutes
  • BI Consultants
  • Artificial Intelligence Software Engineers
  • Machine Learning Consultants
  • Software Engineers
  • Data Analytics Manager

Day 2

Using Decision Trees to identify risky bank loans (2hrs)

  • 1 hr theory
  • 1 hr practical

Morning Tea (15min)

Using Neural Networks to predict the strength of concrete (2.5 hrs)

  • 1 hr theory
  • 2 hr practical

Lunch (30min)

How to Evaluate & Improving Model Performance (3hrs)

  • 1 hr theory
  • 2 hrs practical



75 Featherston St


Wellington 6011

The Instructor/Presenter

DR Mohamed Elwakdy(Ph.D Electrical Engineering); Machine Learning Technical Consultant has over ten years of experience in the area of Machine Learning and data mining with specialisation in Digital Signal Processing, Pattern Recognition and Computer Vision.

He has published many journal articles including:”A Novel Spatial Algorithm for Similar and Non-Similar Trajectories Classification of Different Objects; in: – FECS’15- The 2015 International Conference on Frontiers in Education: Computer Science and Computer Engineering, Las Vegas, USA, 2015.

Published Paper “A Novel Trajectories Classification Approach for Different Types of Ships Using a Polynomial Function and ANFIS; in: – IPCV’15 – The 19th International Conference on Image Processing, Computer Vision, & Pattern Recognition, Las Vegas, USA, 2015.

Published paper ;Speech recognition using a wavelet transform to establish fuzzy inference system through subtractive clustering and neural network (ANFIS); in: – Proceedings of the 12th WSEAS International Conference on Systems, Heraklion, Greece (Jul 22-24; 2008); International Journal of Circuits, Systems and Signal Processing Issue 4, volume 2, 2008 North Atlantic University (NAUN)


None as it an introductory level course

What do you need to bring:

Yourself and a laptop with R Studio installed.

Who is this for:

Students that are new to Machine Learning and want to know what exactly is Machine Learning and how it is used.

What can you expect from the workshop:

If you ever wanted to learn about Machine Learning and what it is. You have come to the right place. This workshop covers basic and introductory Machine Learning concepts to help you get started building your own machine learning models.

Why a practical in class workshop is better than an online course?

You can interact with the tutors and other students in the session that you don’t get with online workshops. Research shows students that receive verbal feedback and constructive criticism from tutors gives students additional motivation to learn.

Most online courses are pre-recorded and cannot give you real time feedback on your exercises that you do. Real time feedback is important because it is most effective in helping you learn something new by reinforcing key ideas and concepts.

In class workshop is also beneficial in ways that it allows students to build relationship and bonds with their peers. This helps them to gain confidence to speak to others and share their opinions and learning experiences. Most employers state that one of the key skills they are looking when they are recruiting is clear communication skills. This is because in a work environment you are working in teams and not just by yourself. Because of this, the Machine Learning Workshop is designed in a way to simulate a work environment and help you build your communication skills.


I really enjoyed the range of models and classifiers that we looked at. I also enjoyed hearing from Mohammed about his research experience and other applications of machine learning. It was good that the facilitators encouraged us to help each other understand concepts. The venue and food were also great.

The people who attended were great to meet, all had a lot of relevant experience in industry and were very engaged.

Please fill in your details to access the Machine Learning Workshop Schedule

Please fill in your details to access the Machine Learning Workshop Schedule

Thank you!!!