This workshop consists of 6 weeks of short presentation of Python principles, basic data analysis and introduction to machine learning, followed up by an assignment which lets the students play around in each topic.

Introduction in Python with:

• numpy
• pandas
• matplotlib

Basic concepts of Data Analysis:

• types of data
• plotting data
• dealling with missing values
• correlation between features and targets

Assignment: Take the avocado dataset and play around with the data, following some tasks like: checking for missing data, grouping the data by different features, checking for categorical data and bringing them to one-hot-encoding format, etc.

Introduction in basic Machine Learning and the types of learners and the description of each type:

• supervised learning
  • classification
  • regression
• unsupervised learning
  • clustering
  • dimensionality reduction
• reinforcement learning

Short description of Simple Linear Regression and Logistic regression.

Preseting Scikit-learn shortly.

Going through the iris dataset and predicting the target value using Logistic Regression.

Assignment: Titanic Dataset - predict if a passenger will survive or not on the Titanic.