Pendahuluan Soft Skills untuk Data Professional (SSDP)

With the advent of automation, humans’ role has become to do what computers cannot. Many more white-collar workers—perhaps all of them—will end up “working with data” to some extent. Using data to provide insights and guidance that computers alone cannot requires “data literacy”, which is doubly important for anyone working alongside, supporting, leading, or hiring a data-science and analytics team.

Issues covered include effective communication, including presentation and communication skills, “storytelling”, and effective listening and elicitation. Technical methods will be presented in the context of their communication value.

Objectives/Content               :

1. An appreciation of the language of data
2. Critical thinking: Never accept the initial answer as the right answer, be skeptical, consider the source, don't get happy ears, embrace struggling, stay curious and have strong appetite to learn, apply the reasonable test, pause to think, embrace productive conflict.
3. Understanding uncertainty (expressed as probabilities) and complexity
4. Interpreting relationships in data (multivariate correlation) and visual representations of them
5. Reading visual representations of data
6. It also includes the ability to think rigorously and abstractly about evidence-based decision-making and manipulate data accordingly.
7. The objective of this course is to enable data scientists and related professionals to communicate better with the rest of the business. This would mean improving their ability to understand what is said to them, and to elicit more information when necessary, as well as to express ideas and findings, to influence and sell more effectively.

Reference                               :

1. Chou, W. (2013). Fast-tracking Your Career: Soft Skills for Engineering and IT Professionals. John Wiley & Sons.
2. Knaflic, C. N. (2015). Storytelling with data: A data visualization guide for business professionals. John Wiley & Sons.
3. Riche, N. H., Hurter, C., Diakopoulos, N., & Carpendale, S. (Eds.). (2018). Data-driven storytelling. CRC Press.
4. Barker, A. (2010). Improve your communication skills (Vol. 39). Kogan Page Publishers.
5. Nossel, M. (2018). Powered by Storytelling: Excavate, Craft, and Present Stories to Transform Business Communication. McGraw Hill Professional.
6. Greenlaw, R. (Ed.). (2012). Technical Writing, Presentational Skills, and Online Communication: Professional Tools and Insights: Professional Tools and Insights. IGI Global.
7. Denny, R. (2009). Communicate to win: Learn the secrets of successful communication and presentation. Kogan Page Publishers.
8. https://astrogrowth.com/critical-thinking-books/
9. Lewrick, M., Link, P., & Leifer, L. (2018). The design thinking playbook: Mindful digital transformation of teams, products, services, businesses and ecosystems. John Wiley & Sons.
10. Pressman, A. (2018). Design Thinking: A Guide to Creative Problem Solving for Everyone. Routledge.
11. Lockwood, T., & Papke, E. (2017). Innovation by Design: How Any Organization Can Leverage Design Thinking to Produce Change, Drive New Ideas, and Deliver Meaningful Solutions. Red Wheel/Weiser.
12. Mootee, I. (2013). Design thinking for strategic innovation: What they can't teach you at business or design school. John Wiley & Sons.

Topic ID	Topic Title	Lessons
SSDP1	Critical Thinking	- Understand the links between ideas. - Determine the importance and relevance of arguments and ideas. - Recognize, build and appraise arguments. - Identify inconsistencies and errors in reasoning. - Approach problems in a consistent and systematic way. - Reflect on the justification of their own assumptions, beliefs and values.
SSDP2	Introduction to Data Scientist Soft Skills.	- Problem solving (data-literacy revisited) - Business acumen - effective communication, - persuasive writing - presentation and communication skills, - “storytelling”, and - effective listening and elicitation.
SSDP3	Data professionals’ leaderships skills	- Highly-efficient Consulting Skills - Understanding barriers to communication - Developing active listening skills - Willpower mindfulness - Building resilience through self-understanding - Meta-skills needed for the 21st century - Innovation thinking - Self-Leadership: Using a map to understand and harmonize one’s psychology - Application of soft skills in the data science setting.
SSDP4	Introduction to Design Thinking	- Introduction to Design Thinking - Design thinking examples - Discovery, Synthesis, Prototype, and Iterate - Tools and strategies - Applications in each division/department

Objectives/Content	:
1	An appreciation of the language of data
2	Critical thinking: Never accept the initial answer as the right answer, be skeptical, consider the source, don't get happy ears, embrace struggling, stay curious and have strong appetite to learn, apply the reasonable test, pause to think, embrace productive conflict.
3	Understanding uncertainty (expressed as probabilities) and complexity
4	Interpreting relationships in data (multivariate correlation) and visual representations of them
5	Reading visual representations of data
6	It also includes the ability to think rigorously and abstractly about evidence-based decision-making and manipulate data accordingly.
7	The objective of this course is to enable data scientists and related professionals to communicate better with the rest of the business. This would mean improving their ability to understand what is said to them, and to elicit more information when necessary, as well as to express ideas and findings, to influence and sell more effectively.