Core Data Science using Python

Exploratory data analysis and interactive visualisation, unsupervised learning, dimensionality reduction and feature extraction, supervised learning and more.

LEVEL: BEGINNER
DURATION: 3-DAY COURSE
DELIVERED: AT YOUR OFFICE

What you will learn

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The course is extremely interactive and hands-on. You will learn by working through concrete problems with a real dataset. You will be taught by academic and industry experts in the field, who have a wealth of experience and knowledge to share

Preprocessing (scaling, log transformations, imputation, one hot coding)
Exploratory data analysis and interactive visualisation
Unsupervised learning (k-means clustering, hierarchical clustering)
Dimensionality reduction and feature extraction
Supervised learning (KNN, decision trees, random forests, SVMs)
Model Evaluation and Tuning
Logistic Regression

Languages and libraries :

Python 3
Numpy and Pandas for data manipulation
Scikit-learn and statsmodel for linear and time series models
Matplotlib for visualisation

PREREQUISITES

Elementary Python programming and use of the command line. You can acquire these skills at our Python bootcamp.

Basic probability and linear algebra.

AUDIENCE

Individuals who want to master new technical skills and learn the latest techniques and industry best practices to work effectively with Data Science teams.

Get in touch with us to learn more about the course! 

DAY ONE

Data Science Essentials

DAY TWO

Unsupervised Learning and Supervised Learning

    • The scikit-learn library for Machine Learning and scikit-learn pipelines
    • k-means clustering
    • Hierarchical cluster analysis
    • Density-based clustering (DBScan)
    • The k-Nearest Neighbour algorithm
    • Overfitting, underfitting, bias-variance tradeoff
    • Cross-Validation and hyperparameter tuning

DAY THREE

Machine Learning

Get in Touch

CONTACT US

We will email you within the next 24 hours to arrange a quick call to help with any questions about the programme and recommend pre-course materials.

We look forward to speaking with you.

Dr. Raoul-Gabriel Urma

Dr. Raoul-Gabriel Urma

Director