Data Analyst Diploma

Diploma Outline
Today’s world is driven by data. More than ever, companies are striving to understand how to improve their operations by dissecting the data they collect to understand clients’ needs and industry trends.

As a Data Analyst, you could find yourself working within a wide range of organisations across a variety of sectors, but the common denominator is the need to glean insights from data. Data comes in a variety of forms and is stored in a variety of database management systems. And your first and foremost goal is to gather insights from the data. Often, you will be dealing with unstructured data stored in different types of data management systems. To achieve meaningful analytical results, several skills must be mastered.

In this diploma, you’ll gain practical analytical skills as you work through the courses. Not only will you find out more about how data is created and managed, but you’ll also look at the fundamentals of research methods and statistical analysis. You will also develop a strong foundation with the most powerful programming languages available for data manipulation, cleaning, and analysis.

Data Analyst Diploma

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Course Info

Duration 200 hours flexi study or 8 weeks full-time (Full-time based on approx 20-30 hours a week)
Training Type Diploma
Study Type In centre, Online

Awards & Qualifications

Awarded 200 CPD points upon successful completion

Is this course right for me?

This training is ideal for those who are new to data analysis and also appropriate for those who may already be working in tech or data science and would like to specialise and become proficient with the tools and techniques of data analysis.

Awarded 200 CPD points upon successful completion
Duration 200 hours flexi study or 8 weeks full-time (Full-time based on approx 20-30 hours a week)

Course Content

Core Courses

Excel Expert
Our Excel Expert course will provide you with the knowledge and skills to use this popular spreadsheet programme to an advanced level. You’ll learn how to work efficiently with PivotTables and PivotCharts, automate processes with macros, create complex
visualisations of your data, establish connections between various data sources, and use Excel’s data analysis tools to make data-driven decisions.

Data Research & Statistical Techniques
This course has been designed to give learners a strong foundation in data research and statistics. Data analysts are challenged to extract meaningful insights from their data. To learn various strategies toward that goal, this course exposes you to the fundamental
research methodology and modelling concepts that are key to performing robust data analytics, visualisation, and data interpretation. This course also emphasises essential statistical methods.

Python for Data Analysts
Python is an all-purpose programming language. It’s used for a variety of applications, from web / software development, game development, to AI, machine learning, and data analysis. This course aims to tackle every corner of Python the Data Analyst must master.

SQL for Data Analysts
Structured Query Language (SQL) is a programming language used to extract and organise data stored in a relational database. This course aims to help you develop the skills to first identify the critical characteristics of database design and management and then be able to work with relational databases.

R Programming and Statistical Analysis
R is widely recognised as a powerful programming language and environment for data manipulation, statistical computing, and graphical display. It provides a variety of tools and techniques and is easily extensible. R is open-source and a vital tool for
data wrangling and analysis. R includes a robust data handling and storage facility, as well as an extensive, integrated collection of tools for data analysis and graphical display. In this course, you’ll learn the fundamentals of the R programming language using
Jupyter Notebooks and RStudio, while running descriptive and inferential analysis with different types of data structure.

Data Visualisation with Tableau
This course covers best practice for visualising data. Using the right charts and graphics helps tell the story that the data has revealed and identify patterns and trends within the data. In this course, you’ll explore essential types of analysis, visualisation, and graphic
tools useful for conveying meaning from your data.

Fundamentals of AI & Machine Learning
This course seeks to provide you with the essential concepts that will allow you to operate in a modern and sophisticated environment. The world of artificial intelligence (AI) includes many areas in computing, which makes it a complex field, combining computer science and robust datasets to enable problem-solving. AI leverages computers and machines to mimic the problem-solving and decision-making capabilities of the human brain.

Project Management for Data Analysts
This course aims to introduce you to the essential tools used in data-driven projects and collaborations. You’ll learn the concepts of Lean, Agile, and Scrum methodologies and their applications.

Course Overview

Aims and Objectives
With this diploma, you’ll acquire a solid foundation of knowledge and skill to become a junior Data Analyst. You’ll work with Python and R, two programming languages widely used in the field of data analysis. And you’ll develop valuable skills with SQL, used for querying databases, and Tableau, which is widely used for data visualisation.

Career Path
There are many options available in this field. You could become a data science professional, pursuing jobs such as data analyst or database developer; or you could go into an analytics-related role, such as business analyst or data-driven manager. The opportunities
are countless!

Pre-Requisites
Successful candidates will be proficient with Microsoft Excel and have a solid background in mathematics (e.g., algebra) and strong critical-thinking and problem-solving skills. Previous exposure to coding is a plus.

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