Workshop: Datascience in a day

*** Minimum 2 Years experience required in the software Field, others please excuse *******

This workshop will teach Python in notebooks and the minimum statistics needed to understand data mining activities and one predictive algorithm. During the workshop, participants will learn how to use Jupyter notebooks to load, visualize, and manipulate datasets. They will also learn about data preprocessing, including handling missing data and feature scaling. The workshop covers various data mining techniques like clustering, classification, and association rule mining.

The workshop then delves into the basics of machine learning, including its applications and types of algorithms. Participants will learn about the difference between supervised and unsupervised learning, the importance of feature selection and hyperparameter tuning, and various machine learning algorithms, such as neural networks, support vector machines, and random forests.

Following the introduction to machine learning, the workshop covers the basics of one predictive algorithm, such as linear regression or decision trees. Participants will learn how to train and evaluate the algorithm and use it to make predictions. Additionally, they will learn about the various evaluation metrics used to measure the algorithm's performance.

Overall, the "Data science in a day" workshop provides a comprehensive introduction to data science and machine learning, covering the necessary concepts, tools, and techniques to get started with analyzing and interpreting data.

**To fully participate in this workshop, it is recommended that attendees have a laptop with at least an i7 processor or a similar configuration and a minimum of 16 GB of RAM.**

**Please take care of your lunch. It will not be provided**