This course aims at making you familiar with basic machine learning approaches and data analytics techniques by enabling you to use them to your professional benefit. Adopting a user perspective, you will learn to automate simple, but time-consuming tasks such as classification of analysts’ conference calls into economically meaningful content.
Additionally, the course enables you to tackle complex prediction tasks using different information sources. Finally, the course gives you relevant data analytics skills such as the description, visualization and statistical analysis of such predictions. We will use the programming language Python to apply the above concepts.
All essential programming skills are taught in this course and there are no prior programming skills required.
The course contains the following building blocks:
2. Introduction to Python
- Python Basics for Data Science
- Importing and cleaning data
- Natural language processing
3. Machine Learning
- Unsupervised machine learning
- Supervised machine learning
- Evaluation of the prediction model
4. Data Analytics
- Data Visualization
- Data description
- Statistical analysis