Data Literacy

Before embarking on the data journey, organizations need to be equipped with the right skills and be data literate. This course walks through that journey and empowers individuals with the skills required to get an organization ready.

No pre-requisites are required to attend this course


What Data Literacy is all about and its importance

Overview of data sources, where data can be obtained from and how data can be collected

Fundamental elements of data

How to ask questions from data

Data Analytics – Foundations, Basic Statistics, Reasoning

Data Complexity, Relationships in Data and Inference

Data Analytics – Foundations, Basic Statistics, Reasoning

Data Complexity, Relationships in Data and Inference

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Course Outline

The first step before diving into the complex operations with data is to understand what data is all about and why it is important for any organization or business to be data literate. This module explores those perspectives.

What does it mean to be Data Literate?

Data Literacy Roadmap and adoption

Why data is important for any organization?

What can be done with data?

Diving deeper into the data literacy roadmap, the primary resource where things start off is the data. It is important to know where data can come from and how data should be collected. This module covers the in-depths of this process.

Data Touchpoints

Data Collection Methodologies

How clean should the data be made?

Typical Data Cleaning and Transformation techniques

Data is all about asking questions and building up the business value. This module covers how and what kind of questions should be asked from the data. It is important not to miss out on asking any critical questions which may help the business.

Defining a business problem

What parts of the data are important?

How do you formulate questions from the important part of the data?

Answering the questions through the data

In order to uncover insights using statistics and other techniques, it is imperative to know how it can be applied to the data and what it can give you. This module solely focuses on establishing foundational analytics and exploring relationships in data.

The Analytics Roadmap for a Business

What does Analytics consist of?

Does Analytics involve Statistics? Understanding important statistical concepts

Exploring relationships in the data using statistical and non-statistical methods

Data in textual format is not the best way to derive insights and understand data. Visuals, Charts & Graphs always appeal to a wider audience because it makes the data easier to understand and comprehend. In this module, we will learn what data visualization is all about and the best practices with Data Visualization.

  • What are the various types of visualizations available?
  • How do we link data to visualizations? Choosing the right kind of visual for the right context
  • Deriving insights from visualizations
  • Best practices of data visualizations
  • Exploring Business Cases

Communication is key with data. Being able to narrate a story with your data through your visuals and business insights is critical to everyone. This module focuses on how a story can be developed from dashboards and visuals and how this should be communicated to different kinds of audience.

Why is Data Storytelling important?

How to identify your audience?

Key elements of Data Storytelling

Pitfalls of Data Storytelling

Exploring Narrations

The end goal with data is always to drive value and gather insights. Ultimately, any organization would want to take decisions based on the gathered insights to help the business. This module helps you understand, through various business cases, how that value can be derived and how decisions can be taken based on the data.

Visual and data informed decision making

Decision making techniques

There’s a lot more that can be done with the data, especially by employing new techniques and advanced analytics. This module gives you an overview of how predictive analytics, machine learning and other technologies can help you maximize the use of your data.

Introduction to Predictive Analytics

Introduction to Time Series

What Machine Learning is all about?

Application of Machine Learning to Business

What’s next with data?

Looking for something else?

Python for Data Science

Python is one of the most important programming languages used across data analytics, data science and machine learning today. This course will take you through the fundamentals of this language.

Machine Learning with Python

Being able to predict the events in the future is a great asset to any business. This workshop focuses on how Python can be used for predictive analytics using various Python libraries.

Computer Vision using Python

Ever wondered how autonomous vehicles work? This course trains you on the fundamentals of image processing, classification and computer vision using opencv and tensorflow.

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It's time to upskill for the Industry 4.0