Data Analytics course

Course description

Analyze data to win essential insights into people’s behavior and trends. You will learn how to analyze datasets and visualize your conclusions. You will also get an introduction to machine learning.

The Data Analytics course is the advanced course of the Data Analytics track.

Outline
  1. Data Analysis

    1. Basic and composite built-in data types

    2. Introduction to series

    3. DataFrames. Indexing and slicing

    4. Missing values

    5. String processing and regex

    6. Groupby and aggregation

    7. Joins & concat/unions

  2. Visualization

    1. Types of Plots

    2. Intro to Matplotlib and Seaborn

    3. Customize your plots

  3. Introduction to ML

    1. Introduction to the ML Pipeline

    2. Inspection of dataset and classification workflow

    3. Logistic regression

    4. Decision trees and random forests

    5. Clustering

Commitment

Students are expected to commit a minimum of 10 hours per week - including attendance to the course (4 hours/week) and self-learning at home (6hours/week). 80% attendance of the course is required for graduation.

Dates

The Onboarding Week takes place in the second week of September.

Semester starts in September and ends on December.

Classes are Monday and Wednesday, 19:00 - 21:00

Interested in the course?

Join our Open Day to find out more about the course and the application process.