This course is designed for professionals who want to enhance their critical thinking and data analysis skills. It is suitable for anyone who is involved in or interested in working with data, such as analysts, managers, consultants, researchers, or developers.

• Define critical thinking and data analysis and explain their importance and benefits
• Apply various critical thinking techniques to analyse information, generate ideas, and evaluate arguments
• Apply various data analysis techniques to transform, model, and visualise data
• Identify and avoid the common pitfalls and biases that affect your thinking and data analysis
• Use appropriate tools and frameworks to support your thinking and data analysis process
• Communicate and collaborate effectively with others to make better decisions

Day One:
Introduction to Critical Thinking and Data Analysis

• What is critical thinking and why is it important?
• What is data analysis and why is it important?
• How are critical thinking and data analysis related?
• What are the benefits of critical thinking and data analysis for professionals?
• What are the challenges of critical thinking and data analysis in today’s business environment?
• What are the common pitfalls and biases that affect critical thinking and data analysis?
• How can we overcome them?

Day Two:

Critical Thinking Techniques

• What are the elements of critical thinking?
• How can we use logic, arguments, evidence, and assumptions to analyse information?
• How can we use creative thinking to generate new ideas and perspectives?
• How can we use systems thinking to understand the big picture and the interrelationships among components?
• How can we use root cause analysis to identify the underlying causes of problems?

Day Three:

Data Analysis Techniques

• What are the stages of data analysis?
• How can we transform data using methods such as cleaning, filtering, aggregating, or merging?
• How can we model data using methods such as regression, classification, clustering, or association?
• How can we visualise data using methods such as charts, graphs, maps, or dashboards?
• How can we interpret data using methods such as descriptive statistics, inferential statistics, or hypothesis testing?

Day Four:

Tools and Frameworks for Critical Thinking and Data Analysis

• What are some of the tools and frameworks that can help us with critical thinking and data analysis?
• How can we use SWOT analysis to assess the strengths, weaknesses, opportunities, and threats of a situation or solution?
• How can we use PESTLE analysis to examine the political, economic, social, technological, legal, and environmental factors that affect a situation or solution?
• How can we use Porter’s five forces analysis to evaluate the competitive forces in an industry or market?
• How can we use SMART criteria to set specific, measurable, achievable, relevant, and time-bound objectives or goals?

Day Five:

Communication and Collaboration for Critical Thinking and Data Analysis

• Why is communication important for critical thinking and data analysis?
• What are the principles of effective communication for critical thinking and data analysis?
• How can we communicate clearly, concisely, confidently, convincingly, and courteously with different audiences?
• How can we use various communication methods (e.g., written reports, oral presentations) to convey our findings or proposals?
• How can we use feedback to improve our communication skills?
• Why is collaboration important for critical thinking and data analysis?
• How can we work with others to solve complex problems effectively?

To enhance learning and practical application of concepts, the training course will use a combination of interactive lectures, case studies, group discussions, practical exercises, and real-world examples. Participants will also get the chance to collaborate on group projects and create action plans adapted to the needs of their respective organizations.