Introduction to Data Science

This course will introduce you to data science concepts, tools, and techniques used in business for data-driven decision-making. You will emerge from it with an understanding of what data scientists do, how they do it, and how your business will benefit from employing data science.

Introduction

Data science lies at the core of our digital society. This course will introduce you to data science concepts, tools, and techniques used in business for data-driven decision-making. You will emerge from it with an understanding of what data scientists do, how they do it, and how your business will benefit from employing data science. Data science involves developing methods of recording, storing, and analysing data to effectively extract useful information. We use data science to gain insights and knowledge from any type of data — both structured and unstructured. Data science involves working with big data. Big data is a huge collection of data and it is growing exponentially. Big data is so large and complex that none of the traditional data management tools is able to store it or process it efficiently. This requires an understanding of how value and information flows in a business, and the ability to use that understanding to identify business opportunities.

 

Overview

Data science is an interdisciplinary field that uses statistical modelling to uncover patterns in data that lead to key insights about businesses and their operations, and can test how changes to particular variables will influence markets, performance and other factors.

Data scientists write programs to model organisational and experimental data, and so must also master real-world business and organisational-based scenarios to be able to evaluate the performance of their models.

On completing this course you will have a good idea of what data scientists do, and understand how your organisation can take advantage of data analysis and machine learning.

Who is it for?

Executives who need to get up to speed quickly with key points of importance in data science; entrepreneurs who want to use fact-driven analysis to optimise their resource-use and make better decisions.

Certificates are awarded on the following basis:

  • Certificate of completion: Cumulative average of 80% in online tests
  • Certificate of participation: Cumulative average of 50%-79% for online tests
  • Certificate of attendance: Cumulative average of less than 50% for online tests

Learning outcomes

You will emerge from this course knowing:

  • How data science affects society;
  • The value of data – and who owns it;
  • What the IT sector around the world is doing to protect data;
  • What an efficient data scientist does;
  • The life cycle of a data science project;
  • Sources of data and collection methods;
  • Mathematical terms frequently used in data science;
  • How data is classified and analysed;
  • Machine learning techniques;
  • How to manage your data science team;

And knowing the importance of:

  • Data ethics;
  • Data security; and
  • Data privacy.

You will cover

Key terms and mathematics in data science; establishing a data science team and managing it; structuring a data science project from data gathering, analysis and visualisation to feature engineering; bias and variance trade off; A/B testing; model deployment and retraining; data ethics, privacy and ownership.

Course prerequisites

  • Basic understanding of algebra and geometry;
  • Basic knowledge of statistical and mathematical terms; and
  • A grasp of the role data plays in business.

Job opportunities

  • Project manager; product manager; presales and sales executive; directors; software architect; business analyst.

DELIVERY OPTIONS

Overview

Participants will engage with the course through recorded classes and supporting content online

What you will get 

  • 16 hours of on-demand video
  • Study notes accompanying the video recordings
  • Practical tasks and digital assessments
  • Online access any time for the duration of the course
  • Certification

Course fees
R 400.00

Course Curriculum

Time: 4 weeks
Curriculum is empty

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