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Fundamentals of Data Science is a three day overview course which blends discussion and group exercises to explore the field of data science with applied real world examples and projects.

Teaching begins with a conceptual introduction to science, data science, big data and machine learning; followed by a litany of real-world data science and machine learning examples.

The remainder is divided into two parts: introduction to Python, and the application of the language in building a Machine Learning model (including data preparation, statistical tests, feature engineering, modelling and evaluation).

Delegates attending this course should have technical skills such as application or SQL programming – expose to Python or R would be advantageous.

01 Introduction to Data Science

To better understand whether you want to become a data scientist
To work with colleagues who are data scientists
To judge whether your team (or organization) could benefit from data science

02 Data Science Project Examples

03 Jupyter Notebook

Practical Lab Activities

04 Introduction to Python

Practical Lab Activities

05 Introduction to Datasets in Python

Practical Lab Activities

06 Introduction to Machine Learning

To understand what these are, what the different types are and some examples of what they are used for.

07 Introduction to Dataframes and Databases with Python

Practical Lab Activities

08 Exploratory Data Analysis with Python

Practical Lab Activities

09 Introduction to Big Data

To better understand what skills need to be developed
To choose the right tools to suit organisational needs
To develop a strategy for working with Big Data

Upcoming Trainings

Join our public courses in our New Zealand facilities. Private class trainings will be organized at the location of your preference, according to your schedule.

Classroom / Virtual Classroom

06 November 2024