This is the brand new version of the hugely popular “Data Science for Developers” training. After two years of teaching thousands of Engineers around the world, this training has been rebuilt from the ground up to squeeze in more information, have bigger theories and provide better positioning.
In this beginner-level course, we will start the day by establishing what Data Science is and how it is used by companies large and small. You will learn about how to develop a Data Science project and how it differs from “normal” Software Engineering. Note that I use the word Data Science to encompass Machine Learning (ML), Exploratory Data Analysis (EDA), Data Mining, Analytics, Deep Learning, Artificial Intelligence (AI), etc. etc.
Next we will cover the “three key phases of Data Science”: data cleaning, modelling and evaluation. With these fundamentals, along with the extensive practical worksheets, you will be able to undertake and succeed in a simple Data Science project.
This training is unique, because nowhere else do you see Data Science laid bare. The materials emphasise the common themes between algorithms, which helps Data Science “click”. Mathematics is avoided as much as practical to instead provide an intuitive understanding.
Who will benefit
- Engineers needing an introduction to Data Science.
- People that want to understand the tools and technologies behind the hype.
- Beginner Data Scientists wanting end-to-end practical experience and industry insight.
What you will achieve
The day is split into two halves. The first part of the day will provide an overview of how Industry uses Data Science and what is expected of its Data Scientists. You will learn how to organise a Data Science project. You will learn about the tools and technologies involved. Along the way we will develop a Data Science plan for either a current project or your career. You can use this to plan and prioritise what you need to learn.
The second half of the day delves into the three key phases of Data Science. Data cleaning, modelling and evaluation. Here we spend a lot of time with practical examples to expose you to the typical Data Science workflow.
This high-level industry-leading overview of how and where you can use data science combined with low-level experience provides a unique learning experience.
Topics covered in this training
- Technical Overview
- Phase 1: Introduction to Working With Data
- Visualising data
- Scaling data
- Dealing with corrupted data
- Phase 2: Introduction to Modelling
- Phase 3: Introduction to Evaluation
- Numerical evaluation
- Visual evaluation
- Many in-depth practical examples demonstrating the day’s concepts
- No (zero) Data Science experience
- Some programming experience
- Preferably with Python (help will be provided)
What You Need to Bring
- A charged laptop. Workshop resources are online and sometimes we have a lack of power sockets.
- A good night’s sleep
- Humility and a smile