Hurry! Save 10% on select upcoming courses! Enrol before 31st January.
Hurry! Save 10% on select upcoming courses! Enrol before 31st January.Download Brochure
Choose Your Start Date
Browse our upcoming live online classes. Download your brochure to learn more.
Starts 18 Jan — Ends 08 Mar 23
- Live online tutorials with an industry expert, plus additional self-directed learning
- 8 weeks: One 1 hour tutorial & 4 hours of self-study per week
- Wednesdays, 6.30pm - 7.30pm
Secure your place with a 5% deposit and pay the rest in instalments. Flexible payment options available.
Why UCD Professional Academy?
- Valuable, trusted qualification
- Industry expert lecturers
- Flexible learning options
Data Analytics for Finance Course Modules
Working on DataCamp’s world-class interactive learning platform, you will learn mission-critical financial analysis skills such as evaluating stock performance or calculating returns for various time horizons - accurately and efficiently. You will develop hands-on Python programming skills and an understanding of how Python tools are used to import and manage data. Weekly mentoring sessions with a data analytics industry expert will help translate this theoretical learning into practical, job-relevant knowledge.
Or browse our wide range of expert-led online courses and grow your career potential today.
1. Introduction To Python For Finance
Discover how Python is used for financial analysis. Learn Python data structures such as lists and arrays, as well as powerful ways to store and manipulate financial data to identify trends.
- Python Introduction
- NumPy arrays
2. Intermediate Python For Finance
Learn how to use Python data structures, execution control statements, and DataFrames to manipulate financial data. Work with pandas, using data from the Federal Reserve Bank to explore national economic trends.
- Datetimes and dictionaries
- Control flow and logic
- Pandas DataFrame
- Working with NASDAQ stock data
3. Manipulating Time Series Data In Python
Learn the basics of manipulating time series data - data that are indexed by a sequence of dates or times. Learn how to calculate rolling and cumulative values for times series.
- Time series in pandas
- Time series metrics and resampling
- Rolling and expanding metrics
- Building a value-weighted index
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
5. Importing And Managing Financial Data
Learn how to bring data from Excel into pandas, and back. Work with APIs. Learn to calculate returns for various time horizons, analyse stock performance by sector, and calculate and summarise correlations.
- Importing data from Excel
- Importing data from the web
- Summarising and visualising
- Aggregating and describing by category
6. Joining Data
Learn to combine and work with multiple datasets and discover why pandas is a cornerstone of the Python data science ecosystem, working with World Bank and City of Chicago datasets.
- Data merging basics
- Merging tables and join types
- Advanced merging and concatenating
- Merging ordered and time-series data
Learn how to use the powerful Python data visualisation library, Matplotlib. Create rich visualisations of many different kinds of datasets and learn how to customise, automate, and share them.
- Introduction to Matplotlib
- Plotting time-series
- Quantitative comparisons and statistical visualisations
- Sharing visualisations with others
8. Machine Learning for Finance
In this course, you'll learn how to calculate technical indicators from historical stock data, and how to create features and targets out of the historical stock data. You'll understand how to prepare our features for linear models, xgboost models, and neural network models. Use linear models, decision trees, random forests, and neural networks to predict the future price of stocks in the US markets. You will also learn how to evaluate the performance of the various models we train in order to optimize them, so our predictions have enough accuracy to make a stock trading strategy profitable.
- Linear regression
- Neural Networks
- Deep Learning
What our Alumni Say about Data Analytics for Finance
Certificate in Data Analytics for Finance was a great introduction to the world of Data Analytics. We got some exposure to all aspects of data analytics tools and systems. The case studies were focused around the financial world. I would definitely recommend the course as it gives a great overview of what data analytics is all about.
Associate of Payment Operations
The Certificate in Introductory Data Analytics was a very good experience. I learned a lot! I got a good foundation in the subject and I now have the skills and guidance on how I can progress in the area, while implementing what I have learned to my current role.
Accounts Assistant, Nicholas O'Dwyer Ltd
I found the Certificate in Data Analytics for Finance to be both challenging and informative. Learning how to use Python was one of the biggest benefits of the course, given that it’s a glue coding language and can be applied elsewhere. The course - alongside my existing experience - will be such a stepping stone into a career in Data Analytics.
Credit analyst, Maynooth University
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.Download Brochure
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Frequently Asked Questions
Is this course right for me?
Although basic financial concepts are covered, this course is not about learning deeper financial theory but rather the practical skills needed to import, clean, format, and visualise financial data using Python programming language, tools, and libraries.
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.
How will this course help with my career?
The financial services industry relies heavily on data analysis to solve complex problems and reduce risk. Financial institutions depend on data from different sources and need skilled analysts to import, manage, and derive meaning from it.
Throughout this course, you will work with multiple real-world datasets from, for example, the World Bank, NASDAQ, AMEX, and Google, allowing you to demonstrate your hands-on experience and skills to potential employers.
What is the online learning experience like?
Outside of your mentor sessions, students will need to complete some self-study work using the DataCamp platform.DataCamp is a world-class learning platform for building data skills. Because you access it online, the tools are available anytime, anywhere. No need for bulky, costly software, just run code in your browser.
Learning is supported by live weekly 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 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 are the benefits of a Professional Certificate?
UCD Professional Academy certificates and awards 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 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 Awards & 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 qualification to your LinkedIn profile.
What payment options are available?
A place on any of our programmes can be secured with a 5% deposit.
For full-time (boot camp) programmes, the balance must be paid in full before course commencement.
For part-time programmes students will be required to pay 45% of the fees before the start of the course, with the remaining balance due within 30 days of the course commencing.
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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