Data Analytics

Start dates:
Classroom: 17 September 2024
Online: 17 June 2024

Venue:
• Dublin Chamber of Commerce. 7 Clare Street, Dublin 2, D02 F902.
• Online

€1,495
• To secure your place on the course a deposit of €296.00 is required.
• The remainder of the course fee €1,199.00 is due 30 days prior to the commencement of the course.
• All fees must be paid before the course begins.
• Please note, the full course fees are inclusive of all course materials and certification costs.

We want to make education easy and enjoyable for you. At Fitzwilliam Institute, we offer a range of finance options to suit your needs.

You can buy now and pay later with humm - humm provides a simple application process, simple terms and conditions, up to 36 monthly payments. With low-interest rates.

Online Application Form

Enrolment intake is strictly limited on this course. Early application is advised. Places are allocated on a first come first served basis.

Diploma in Data Analytics
• Over 3 months of intensive high-level data analytics training with interactive modules covering: Describing and examining data in which individual attributes can be described and summarized: the scales on which they are measured, how to describe their center as well as the variation using descriptive statistical approaches, and how to make statements about these attributes using inferential statistical methods, such as confidence intervals or hypothesis tests, etc.
• Practical skills training delivery from leading industry professionals. All of Fitzwilliam Institute’s data analytics trainers are top industry professionals with many years of successful data analytics experience. Fitzwilliam Institute’s data analytics course contains the core and vital Python and “R” programming industry key skillset and, on completion, all of our students are ready for their data analytics career.
• Real life data analytics programming briefs. Fitzwilliam Institute’s Diploma in Data Analytics offers practical and specific Python programming skills that can be applied in real world situations. You will complete a real life data analytics programing brief, which will help you gain invaluable data analysis experience and develop your work portfolio. A combination of interactive group sessions, presentations, and questions and answers allows you to gain transferrable skills and invaluable experience, in real-life situations, which will prepare you for a successful future in the industry.
• Data analytics jobs, networking and volunteer opportunities. Fitzwilliam Institute is extremely well placed within the Information Technology field. Employers are always looking for Fitzwilliam Institute’s data analytics students and alumni – that’s why they come to us first to hire. Fitzwilliam Institute’s website features a comprehensive jobs and volunteer opportunities section.

On successful completion of this course you will receive a Professional Diploma qualification that is certified and awarded by the ICM (Institute of Commercial Management).

• Basic Statistics
Descriptive statistics; inferential statistics; graphical summaries;

• Working with Python Programming Language
Functions and graphics in Python programming language;

• Introduction to Python Programming
Use built-in data structures such as lists, dictionaries, and tuples to perform increasingly complex data analysis;

• Using PyCharm
Basic use of PyCharm interface; the Python libraries used will be Pandas, Numpy, SciPy, Matplotlib;

• Statistical Testing
Deciding whether data supports your assumptions; types of statistical tests; one and two sample tests;

• Regression Analysis
Understanding relationships with a linear pattern; simple linear regression and multiple linear regression; model diagnostics;

• Analysis of Variance
Understanding one-way and two-way analysis of variance ANOVA;

• Types of Probability Distributions
Understanding probability; different probability distributions - Gaussian; Binomial; Gamma and Poisson;

• Data Mining
Analyzing data while looking at multiple variables simultaneously; clustering techniques; k-means algorithm;
• Introduction to R Programming and R Studio
Functions and graphics in “R” programming language and use of the RStudio;

• Classification Analysis
Analyzing data when the outcome of interest is binary; logistic regression and decision tree algorithm;

• Machine Learning
The process of developing, testing; applying predictive algorithms to achieve future outcomes; understanding random forest algorithm;

• Simulation / Model Validation
Determining the accuracy of competing models; assessing model fit; selecting best model;

• Time Series Analysis
Analyzing and predicting data over time; understanding and using time series data

Tel: (01) 283 4579
Email: info@fitzwilliaminstitutegroup.ie