Designed With — and for — Data Professionals
Concentrate on the most important tools for data scientists on the job. GA’s data science advisory board regularly curates the best practices and innovative teaching approaches of our entire expert network to emphasise real-world relevance and meet evolving employer demands. Its work ensures that students graduate ready to tackle the challenges they’ll face in the field.
Harness the Predictive Power of Data
Tailored for students with quantitative or programming backgrounds, this course dives into the essentials of data science: Python programming, exploratory data analysis, data modelling, and machine learning. Get the hands-on experience you need to synthesise extremely large data sets, build predictive models, and tell a compelling story to stakeholders.
Practice the fundamentals of evidence science by practising basic functions in Python.
- What is data science
- Your development environment
- >Foundations of Python
Research Design and Exploratory Data Analysis
Practice exploratory data analysis for cleaning and aggregating data and understanding the basic statistical testing values of your data.
- Exploratory data analysis in pandas
- Experiments and hypothesis testing
- >Data visualization in python
- Statistics in python
Create linear and logistic regression models, and branch from statistics into machine learning with kNN and classification.
- Linear regression
- Train-test split
- KNN and classification
- Logistic regression
Learn and practice core machine learning models to evaluate complex problems
- Decision trees and random forests
- Working with API data
- Natural language processing (NLP)
- Time series