This three day course is aimed at those who are familiar with the essentials when working with data and are interested in learning about how Data Science, Analytics, Machine Learning, and Artificial Intelligence (AI) can be used to yield value from data assets.
This course will be of interest if you are interested in developing your own skills to move from analytics to Data Science, or if you are supporting organisational digital change, or if you are working with Data Scientists and want to learn more about what’s possible.
You will be introduced to key concepts and tools for use in Data Science, including typical Data Science Project lifecycles, potential applications & project pitfalls, relevant aspects of data governance and ethics, roles and responsibilities, Machine Learning and AI model development, exploratory analysis and visualisation and strategies for working with Big Data.
Throughout the course you will engage with activities and discussions with one of our Data Science technical specialists. Two of the course modules will allow you to complete ‘low or no’-code practical labs in order to test and compare the capabilities of Python and R, and to see a Machine Learning or AI workflow using Orange – giving you enough to start some ideas flowing and try things in your workplace or continue learning on one of our technical training routes into Data Science, Machine Learning, and AI with a firm grounding in key Data Science concepts.
We recommend that delegates are familiar with fundamental data concepts, such as those found on our QA Data Fundamentals programme. You should also have an interest in developing Data Science within your organisation or in becoming a Data Scientist. No prior coding experience is required.
Members of the audience are not required to have a high level of technical expertise, but should be familiar with fundamental concepts for Data, such as table structure.
They may be Mid/Senior Leadership seeking a greater understanding of how to implement Data Science within their organization.
They may come from other technical backgrounds such as Data Analysts, Software Developers, and Data Engineers who either work with Data Scientists or are using this course to begin a journey towards training as a Data Scientist.
In the latter case, audience members may ask for recommendations for their next steps in training towards becoming Data Scientists. We recommend the following refreshed courses which are due to launch in 2023 and 2024 in this suggested sequence:
Introduction to Data Governance
Introduction to Data Science and the Data Analytics Lifecycle
Introduction to Machine Learning
R and Python Taster
Identify development environments for R and Python.
Exploratory Data Analysis
Data Visualisations for Analysis
Interpreting Data Science Dashboards
Legal and Ethical Considerations for Data Analysts
Organisational Data Strategy
Introduction to Big Data
Professional Standards for Data Scientists
Welcome and course administration
Feedback and course close
Join our public courses in our Istanbul, London and Ankara facilities. Private class trainings will be organized at the location of your preference, according to your schedule.