Early Bird: Save 10% when you enrol before 30th April.

Early Bird: Save 10% when you enrol before 30th April.

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Certificate in Introductory Data Analytics

Self Study + Live Online Learning

Develop your data analysis skills with a Certificate in Introductory Data Analytics. With this course you can become a valuable contributor to your organisation’s decision-making process. The demand for data science skills far outstrips supply as organisations increasingly rely on data and insights to drive economic growth, innovation, and digitisation.

  • Bundle & Save. Book 2 or more courses and save 15%.

Hurry! Early Bird 10% off. Enrol before 30th April. Download the brochure now to reveal your discount code.

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Browse our upcoming live online classes. Download your brochure to learn more.

Secure your place with a 10% deposit and pay the rest in instalments. Flexible payment options available.

Why UCD Professional Academy?

  • Valuable, trusted certification
  • Industry expert lecturers
  • Flexible learning options

€49,000 / Annual

Data Analyst Salary in Ireland

The average Data Analyst salary in Ireland is €49,000 per year. Entry level positions start at €35,000 per year while more experienced developers make up to €56,000 per year.

Salary data source: indeed.com, 11th January 2023

Average
€49,000

Salary data source: indeed.com, 11th January 2023

Introductory Data Analytics Course Modules

This interactive, hands-on course will give you a thorough grounding in the algorithms, methods, and tools that can be used to analyse and understand large datasets.

Using Python programming language on DataCamp’s world class learning platform, you will process data – importing, cleaning, formatting, and manipulating it – and then create data visualisations to present different kinds of information. Weekly mentoring sessions with your data analytics industry expert will help translate this theoretical learning into practical work-based knowledge. This qualification will prove to potential employers that you are a skilled professional who can help them derive meaning and value from the large volumes of data they hold.

Or browse our wide range of expert-led online courses and grow your career potential today.

1. Introduction To Python

Learn why this general-purpose programming language is so popular for data science. Discover helpful data science tools and powerful ways to store and manipulate data. Begin conducting your own analyses.

  • Python concepts and data types
  • Use lists to organise data
  • Use functions, methods, and packages
  • Work with the NumPy array

2. Intermediate Python

Learn key concepts such as Boolean logic, control flow, and loops in Python. Bring together these core skills to solve a case study using hacker statistics.

  • Data visualisation with Matplotlib
  • Dictionaries and the pandas DataFrame
  • Logic, control flow, and filtering
  • Looping and iteration
  • Case study: hacker statistics

3. DataFrames

Explore all the core data science concepts with pandas, the world's most popular Python library. Manipulate DataFrames as you extract, filter, and transform real-world datasets for analysis.

  • DataFrames and fundamental manipulations
  • Aggregating data
  • Slicing and indexing
  • Creating and visualising DataFrames

4. Version Control

Version control is one of the power tools of programming. It allows you to keep track of what you did when, undo any changes you decide you don't want, and collaborate at scale with other people. This course will introduce you to Git, a modern version control tool that is very popular with data scientists and software developers, and show you how to use it to get more done in less time and with less pain.

  • Basic workflows
  • Repositories
  • Undo
  • Branches
  • Collaborating

5. Importing Data

As a data scientist, you will need to clean data, wrangle and munge it, visualize it, build predictive models, and interpret these models. Before you can do so, however, you will need to know how to get data into Python. In this course, you'll learn the many ways to import data into Python: from flat files such as .txt and .csv; from files native to other software such as Excel spreadsheets, Stata, SAS, and MATLAB files; and from relational databases such as SQLite and PostgreSQL.

  • Flat Files
  • APIs
  • Relational Databases
  • SQL

6. Joining Data

Learn to handle multiple DataFrames by combining, organising, joining, and reshaping them using pandas. You'll again work with real-world data sets (the World Bank and the City of Chicago).

  • Data merging basics
  • Different join types
  • Advanced merging and concatenating
  • Ordered and time-series data

7. Visualisation

Learn to create visualisations for different kinds of data and customise, automate, and share these visualisations. Use Matplotlib and Seaborn in a variety of situations to explore your data and effectively communicate your analysis with visualisations such as scatter plots, box plots, and bar plots. Use Seaborn's sophisticated visualisation tools to analyse multiple real-world data sets. Customise Seaborn plots for your unique needs.

  • Using Seaborn
  • Visualising two quantitative variables
  • Visualising categorical/quantitative variables
  • Customising Seaborn plots

8. Machine Learning

What's behind the machine learning hype? In this non-technical course, you’ll learn everything you’ve been too afraid to ask about machine learning. There’s no coding required. Hands-on exercises will help you get past the jargon and learn how this exciting technology powers everything from self-driving cars to your personal Amazon shopping suggestions. How does machine learning work, when can you use it, and what is the difference between AI and machine learning? They’re all covered. Gain skills in this hugely in-demand and influential field, and discover why machine learning is for everyone!

  • Linear regression
  • Modelling
  • Neural Networks
  • Deep Learning

What does a data analyst do?

A data analyst is responsible for collecting, organising, and analysing data in order to provide insights and support decision-making within an organisation. They manipulate and visualise data, and may also be responsible for building and maintaining databases.

Data analysts often work closely with stakeholders to understand their data needs and help them make data-driven decisions.

What our Alumni Say about Introductory Data Analytics

I would recommend this course because Data Analytics is a top in-demand job today and having the basic skills in this field is always beneficial. Learning to use data and visualise it will be useful in any job! Self-learning was important in this course but there was also the interactive element with the lecturer.

Malvika Oke

Senior Administrator Screening Services, Amazon

I enjoyed the Data Analytics course as I’m a technical person and enjoy the field of Data Analytics in general. The course gave a very good introduction to Python and it has given me the tools to be able to access data online and extract the pertinent information.

I really enjoyed my time doing the Data Analytics course. I think Data Camp was really great and helpful, and my professor was really knowledgeable. The course was very informative and a great jumping off place, so I would absolutely recommend it to others. 

Studying Data Analytics was a very enjoyable experience - it provided interesting insights which I expect to use as I move into coding down the road.

Certificate in Introductory Data Analytics

My Data Analytics course really helped me focus on a possible future career in Data Analytics. I found the detail and the real life focus of the course really useful and the course guided me on what a career on Data Analytics looks like. I would strongly recommend this course!

Exclusive

Access to thousands of journals, articles and papers. Free of charge.

Students taking part in this course will now have access to the EBSCO Online Library, free of charge, for the full duration of the course. Here you can browse thousands of relevant journals, articles and other reliable academic and commercial texts like the Harvard Business Review, Bloomberg Businessweek and Forbes Magazine, to supplement your learning and assignments.

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Frequently Asked Questions

Is this course right for me?

You do not need a prior qualification in data analysis, but you should be comfortable with technology and Excel formulas.We have the follow entry requirements:

  • Basic Computer Skills (Mandatory), 

  • Skills to Install Software from Online Websites (Mandatory), 

  • Understanding of Data and Charts in Excel (Or any related Software to create Charts/graphics)

Good maths skills are a definite advantage for a career in data science. A basic understanding of coding would also prove beneficial. If you don’t have any experience in coding, you may need to spend extra time on self-study. You’re encouraged to discuss this with one of our Education Consultants before booking your place on the course.

You will need a computer capable of running a development environment: a modern 64-bit CPU, with at least 4GB of RAM and 5GB of available storage running a recent or preferably the latest version of Windows, Linux or macOS. If you use a company computer, you may need to check with your IT department to ensure you have access and permissions to install the required software.

Data science is a rewarding career where you will be central to finding solutions to business challenges as well as spotting opportunities. If you'd like to learn more about a career in Data Analytics, check out our article: What is Data Analytics?

How will this course help with my career?

Data science is booming. Data Scientist has been in the top 10 of LinkedIn’s list of Emerging Jobs Report for the past few years, and demand outstrips supply. You will find opportunities in a wide range of sectors, from global tech companies to banking, from healthcare to retail. There are data roles in most industries, plus you can choose to specialise in a particular area (e.g. finance or marketing).

What is the student experience like?

Student care is a high priority at UCD Professional Academy, which is why our Student Services team is on hand to support you throughout your time with us. They will respond to any queries you have, help you with any technical issues, and facilitate your learning experience at every point. All students are given access to our Student Portal, where you can see your timetable, access all your study materials, and manage your account.

What is the online learning experience like?

Outside of your online tutorial sessions, learners will need to complete some self-study work using the DataCamp platform.The DataCamp platform, where you will transform your data skills is trusted by over 6 million learners globally. All of your learning happens in-browser, so there’s no need for installation of heavy and costly software programmes.

Your learning is supported by weekly live expert mentor sessions, delivered using Zoom. During these classes, your teachers will use technology interactively to ensure an engaging learning experience. When appropriate, students will be encouraged to activate their microphones so that they can ask questions and communicate with other students.

Explain the UCD Professional Academy and DataCamp collaboration to me?

DataCamp is a world class learning platform for building data skills online. Unlike other courses, which require you to download bulky and costly software everything happens via your browser, meaning you’ll have access to the very tools to master python skills anytime, anywhere. Check out Datacamp's case study on UCD Professional Academy collaboration.

A weekly one hour mentor session with a data analytics industry expert supports your learning. This helps you take your knowledge and apply it to real world business scenarios to give you practical, applicable skills. Our mentors have first hand knowledge of how to build and develop a career in this exciting field.

How is this course assessed?

If you are studying an online course, your assessment will also be submitted online.

There is no final exam. You will be assessed based on your submission of a report-based project, which will evaluate your understanding of the concepts you have learned. Your project will analyse an open source data set – you will retrieve, manipulate, and process a data set, working with it through the various stages of the course.

What are the benefits of a Professional Academy Certificate?

UCD Professional Academy Certificates and Diplomas are designed to give your career an advantage. Developed in conjunction with industry thought leaders our courses teach practical, applied skills to support you to achieve your career and business goals. Professional Academy Certificates are suitable for career minded learners wishing to advance their professional skills and prospects rather than their academic credentials.

The Professional Academy is an independent wholly owned part of UCD designed to address the need for skills development in the workforce. Courses tend to be short, designed and delivered by industry practitioners, and are not part of nor do they lead to a traditional University award such as a degree or a masters. They are widely accepted by employers and many students are sponsored to study by their organisation.

For full details of UCD Professional Academy’s Certifications & Governance please visit https://www.ucd.ie/professionalacademy/governance/

How do I get my Professional Academy Certificate?

Your UCD Professional Academy Certificate will be issued electronically on a secure platform, with a link that you can share with employers and others wishing to verify your credentials. You can also add this certificate to your LinkedIn profile.

What payment options are available?

A place on any of our part-time & on demand courses can be secured with a 50% deposit with the remaining balance due within 30 days of the course commencing.

For full-time Bootcamp courses, 100% of the course fee should be paid before starting.

Please note that standard terms and conditions apply, which you can review here: https://www.ucd.ie/professionalacademy/terms-and-conditions/

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