Master the essentials of data analysis and visualization, learn to interpret and present data effectively, and gain hands-on skills in data tools, statistical methods, and visualization techniques across four intensive training days.
Course Overview Table
| Chapter | Details |
| Partner | University “St. Kliment Ohridski” – Bitola, Faculty of Information and Communication Technologies |
| Title | Tools for Data Analysis and Visualization |
| Service | Course |
| Target Group | Startups, SMEs, Data Analysts, Business Analysts, Researchers, Marketers |
| Format | In-Person Training, Workshop |
| Focused on Key Technologies | Data Analysis Tools, Visualization Software, Statistical Methods, generative AI tools |
| Status | Ready to offer |
| Stakeholders from SME/PA Side | Data teams, business intelligence units, research departments, marketing teams |
| Requirements for Participation | Basic computer literacy; interest in data analysis or statistics |
| Estimated Duration | 16 hours |
Description of the Course
This 4-day course introduces the principles and practical applications of data analysis and visualization, designed for individuals and organizations aiming to leverage data for decision-making through hands-on experience and expert-led training. Data analysis and visualization are essential skills in today’s data-driven world, enabling businesses and researchers to uncover insights, identify trends, and communicate findings effectively. This course explores popular tools like Python (Pandas, NumPy), Excel, Tableau, and Power BI, with applications in business analytics, market research, and performance reporting.
Participants will learn the complete process of analyzing and visualizing data: collecting and cleaning datasets, performing statistical analysis, and creating compelling visualizations. Key topics include data wrangling, exploratory data analysis, statistical techniques, dashboard creation, and storytelling with data. Attendees will work on real-world projects, such as analyzing a sample dataset and presenting insights through visualizations, to apply their skills.
Tentative Agenda:
Day 1: Introduction, data analysis basics, tool overview, demo of software
Day 2: Data cleaning, statistical methods, exploratory analysis
Day 3: Visualization techniques, dashboard creation, hands-on exercises
Day 4: Working on a real project with data, best practices, and final project showcase
After four days, participants will leave with a functional data analysis project, a solid understanding of data tools and visualization techniques, and the confidence to analyze datasets, create impactful visualizations, and present data-driven insights effectively.
Additional Course Information
| Category | Details |
| Developed skills | Understanding data analysis tools; Data cleaning and preparation; Statistical analysis; Data visualization; Storytelling with data |
| Learning Methods Used | Presentations, live demos, guided practice, Q&A, collaborative projects |
| References/Resources | Python Data Science Handbook, Tableau Public Resources, Microsoft Power BI Tutorials, Excel Data Analysis Guides |
| Overview Slides | [To be attached or linked separately] |