Professional Diploma In Data Analytics Course Price €875. Get 20% off the normal €1095 fee. Flexible installment payment plans are available. Apply Online!
Embark on an exciting journey into data analytics with our Professional Academy Diploma at Dorset College Dublin. This 12-week, part-time online course is designed to equip you with in-demand skills in predictive data analysis and visualisation. Ideal for business professionals, aspiring data analysts, or IT specialists, this programme provides the tools and techniques to make data-driven decisions and unlock valuable insights from complex datasets.
Why Choose This Course?
✔ Expert-Led Live Online Training – Learn directly from industry professionals.
✔ Hands-On, Real-World Projects – Apply your knowledge to practical scenarios.
✔ Career Ready Skills – Gain expertise in Python, data cleaning, statistical analysis,
✔ Machine learning fundamentals, advanced data visualisation techniques and much more.
✔ Flexible & Future-Focused – Learn at your own pace while preparing for high-growth careers in data analytics
This course provides a practical, industry-focused approach to predictive data analytics, equipping learners with the skills to analyse trends, forecast outcomes, and make data-driven decisions that drive business success. If you would like to learn more about any of our courses or have any questions, simply contact [email protected] or call us on (01) 574 6850.
The Python Institute exam (cost included in the course fee) is structured as follows:
✔ PCEP – Certified Entry -- Data Analyst With Python Certification (Exam PCED-30-XX).
The average Data Analyst salary in Ireland is €47,000 per year. Entry level positions start at €35,000 per year while more experienced analysts make up to €55,000 per year.
✔ Python for Data Analytics – Learn programming basics: syntax, variables, and control flow.
✔ Data Preparation & Cleaning – Import, clean, and manage messy data.
✔ Data Manipulation – Use Pandas for data transformation and merging.
✔ Data Visualisation – Create clear, impactful charts and graphs.
✔ Statistical Analysis – Identify patterns and trends in data.
✔ Machine Learning – Understand regression, classification, and predictions.
✔ Data Integration & Reporting – Merge datasets and present insights.
✔ Real-World Data Handling – Import, filter, and export data.
✔ Final Project – Apply skills to a hands-on analysis project.
Week 1: Introduction to Data Analytics and Programming Fundamentals
✔ Explore the basics of data analytics, its applications, and programming concepts.
✔ Set up Python and learn its foundational syntax.
Week 2: Python for Data Analytics Foundations
✔ Learn key Python libraries for data analytics, such as Pandas, NumPy, and Matplotlib.
✔ Understand how to perform basic data manipulation, calculations, and visualisations.
Week 3: Data Importing and Cleaning
✔ Extract and clean data from sources like databases and the internet.
✔ Handle missing or inconsistent data effectively.
Week 4: Dataframes and Data Manipulation
✔ Learn to manipulate and transform large datasets using Python libraries like Pandas.
Week 5: Joining Data and Data Preparation
✔ Combine multiple data sources meaningfully.
✔ Develop skills in feature engineering and data preparation techniques.
Week 6: Data Visualisation with Python
✔ Understand the importance of data visualisation and use Python tools to create impactful visuals.
Week 7: Statistical Data Exploration
✔ Analyse data using statistical methods and summary statistics to uncover patterns and trends.
Week 8: Introduction to Modelling and Machine Learning Basics
✔ Learn the fundamentals of machine learning, including linear regression and classification.
✔ Explore supervised, unsupervised, and reinforcement learning algorithms.
Week 9: Data Importing, Filtering, and Exporting
✔ Import data from formats like CSV and Excel, filter and transform it, and export it in various formats.
Week 10: Presenting Data Effectively
✔ Format data for reports and create clear tables and visuals.
✔ Learn best practices for presenting insights to stakeholders.
Week 11: Final Project
✔ Complete a comprehensive data analysis project, applying skills in data importing, manipulation, and visualisation.
Data Analytics Classes at Dorset College Dublin are now 100% Online: You can now up-skill or re-skill from the comfort of your own home with expert led industry experienced lecturers who will provide you with inspirational lectures and all support materials you need to achieve your goals.
This aim of this course is to develop a solid understanding of data analytics and business intelligence for learners from non-IT and non-technical backgrounds, to equip the learner with essential skills for the entire data analysis process, from problem formulation to data collection, cleaning, analysis, visualization, and interpretation. Learners develop critical thinking and problem-solving abilities to apply data-driven solutions across various fields. The course emphasizes effective communication, enabling clear presentation of insights to technical and non-technical audiences through compelling visualizations and reports.
Assessment is continuous throughout the programme and consists of a personal project, & assignments.
✔ A project (100%) designed to showcase your ability to use Data Analytics with Python.
The Python Institute exam (cost included in the course fee) is structured as follows:
✔ PCEP – Certified Entry -- Data Analyst With Python Certification (Exam PCED-30-XX).
Upon successful completion of the Data Analytics Course, you will receive Data Analytics:
✔ A Diploma In Data Analytics Course Using Python from Dorset College Dublin
By the end, students will identify different data types, select appropriate analysis techniques, perform exploratory data analysis, create visualizations, conduct hypothesis testing, and apply these skills to real-world data.
✔ Mastering data science involves understanding different data types (quantitative, qualitative, structured, unstructured), identifying relevant data sources, and evaluating data quality for biases.
✔ Data preparation skills include cleaning, transforming, and structuring data for analysis.
✔ Exploratory analysis covers calculating descriptive statistics and creating visualisations (histograms, scatterplots, box plots) to explore data distributions and relationships.
✔ Hypothesis testing involves formulating and testing hypotheses, conducting basic statistical tests (t-tests, correlation analysis), and interpreting results.
✔ Effective communication skills are essential for selecting appropriate visualizations, explaining analysis results to non-technical audiences, and creating concise, informative reports.
To secure a place on this course a non-refundable deposit of €150 applies.
Flexible payment plans available.
| Deposit secures your place on the course | €150.00 |
| 1st Instalment: 18/04/2025 | €362.50 |
| 2nd Instalment: 22/05/2025 | €362.50 |
