New course: Data Analysis Fundamentals
In recent years, data analysis has established itself as a new driver of company success! On February 22, our course " Data Analysis Fundamentals” will start. The course is taught by Nicolas Vu Huu, the Head of People Analytics at Bank Vontobel.
What are the advantages of having Data Analysis knowledge?
Data analysis knowledge is necessary to harness the power of data. Data is constantly being generated. Any human interaction with apps on computers, phones, tables, or via wearables generates data. Sensors on cars, trains, drones, lab devices, medical devices and implants, weather stations etc. generate data. With data analysis knowledge, you can source your data, build an understanding of your data, assess its properties and quality, and eventually transform your data to make it fit for machine learning. With data analysis knowledge, you make better decisions about what you can and cannot do with your data. As you go into simulations, machine learning and deep learning, data analysis will also inform key decisions such as which machine learning model to choose and how to tune it.
What is the first step to Data Analysis?
The first step is getting the data. It sounds easier than it is. In practice, one first needs to think about what is needed. Let me give you an example: Imagine you want to optimize irrigation on a farm. You may want to get data from a variety of sensors measuring weather and soil conditions, maybe some weather forecast data, and then combine it with data related to the needs of the crops growing on the farm. You will need to get the data from different systems with different data interfaces and different data formats. Then you may ask yourself how often you need to collect data? Is once per day enough, what about once per hour? With this simple example, you can appreciate some of the challenges of getting the data.
What do participants learn?
In this hands-on course, you will cover the full data analysis pipeline starting with data acquisition. You will practise with Python on real data sets and develop your data literacy. You will learn to think in terms of data processing pipeline and inform your own decisions on data cleansing and data transformation. For the final project, you will also have the chance to work on a topic and data set that are directly relevant to your current work.
Can you give us some application areas?
Data analysis is used in all industries. And I would argue that the ability to use data provides a competitive edge. The application area I work in is people analytics. With people analytics, companies can develop a great place to work where people can strive. For instance, have you ever wondered why one of your colleagues been promoted and not you? With data analysis, it is possible to better understand the structure and evolution of an organization and its people. It is also possible to detect outliers in the data, uncover biases and calibrate data to ensure fair and equal treatment.
Who is the course for?
This course is for you first and foremost for those who like data and want to broaden their data literacy and get familiar with Python. It is foundation course so you do not need any prior work experience with Python. I would also strongly recommend this course to anyone who plans to study machine learning and/or simulations and does not have any work experience with Python.
The course starts on February 22 and takes place in the evenings. Application deadline is Feburary 8. More information and registration: Data Analysis Fundamentals
Learn more about the wide range of continuing education courses offered by the Institute of Applied Simulation in the field of Computational Science and Artificial Intelligence: www.zhaw.ch/ias/continuingeducation