Structured Thinking - Resolving The Problem
Published 6/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.59 GB | Duration: 3h 0m
Published 6/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.59 GB | Duration: 3h 0m
Get your Problem Solving Acumen Right with this Structured Thinking course.
What you'll learn
Analytical thinking - Breaking down complex problems into smaller parts
Problem Solving - Define problem, generate possible solutions, explore alternatives
Critical Thinking - Evaluates arguments, assess assumptions etc.
Decision Making - Assess risks, Select the most appropriate option.
Efficiency: Provides a framework for organizing tasks and Prioritizing
Requirements
Basic knowledge of computer
Description
The Structured Thinking course is an immersive and transformative learning experience designed to develop and refine participants' critical thinking and problem-solving skills through a systematic approach. This dynamic course equips individuals with essential tools and techniques to analyze complex problems, organize information effectively, and communicate ideas with clarity and precision.Throughout the course, participants are exposed to a wide range of frameworks and methodologies that facilitate structured thinking. They learn how to break down intricate problems into manageable components, identify key factors, and discern relationships and dependencies. By employing various analytical techniques, such as decision trees, problem trees, and root cause analysis, participants gain a comprehensive understanding of problems and can develop logical and coherent solutions.The course blends theoretical knowledge with practical application. Participants engage in hands-on exercises and work on real-world case studies, applying structured thinking methods to diverse scenarios. These practical activities enable participants to hone their skills and deepen their understanding of how structured thinking can be leveraged across different domains and industries.Moreover, the course emphasizes the development of critical thinking mindsets and habits. Participants cultivate the ability to think critically, ask probing questions, challenge assumptions, and consider alternative perspectives. They also enhance their communication skills by learning how to present complex ideas in a clear, concise, and compelling manner.
Overview
Section 1: Introduction to Structured Thinking
Lecture 1 Introduction
Lecture 2 Why Structured thinking is required
Lecture 3 3. Who needs Structured Thinking
Section 2: Introduction to the Course
Lecture 4 1. Instructor Introduction
Lecture 5 2. Methodology
Section 3: 3. Structured Thinking for Data Science
Lecture 6 1. Case Study - Problem Solving without Structured Thinking
Lecture 7 2. Feedback on Case Study 1
Lecture 8 3. Case Study - Problem Solving using Structured Thinking
Lecture 9 4. Feedback on Case Study 2
Section 4: 4. Role of Structured Thinking in Data Science Lifecycle
Lecture 10 4. Role of Structured Thinking in Data Science Lifecycle
Lecture 11 2. Structured Thinking at Each Stage of the Data Science Lifecycle
Section 5: 5. Understanding and Defining the Problem Statement
Lecture 12 1. Importance of Defining the Problem Statement
Lecture 13 2. 5-Step Framework
Lecture 14 3. TOSCAR Framework for Defining a Problem
Lecture 15 4. Examples using TOSCAR
Lecture 16 5. Decomposition
Lecture 17 6. Common Pitfalls to Avoid while Defining a Problem
Lecture 18 7. Framing the Problem Statement for the Course
Section 6: 6. Hypothesis Building
Lecture 19 1. What is Hypothesis Building & Framework
Lecture 20 2. Why Hypothesis Building is Important and Who Should be Involved
Lecture 21 3. How to Build a Comprehensive Hypothesis Set
Lecture 22 4. Hypothesis Building Example
Lecture 23 5. Best Practices & Pitfalls
Lecture 24 6. Building Hypothesis for this Course’s Problem Statement
Section 7: 7. Data Extraction and Cleaning
Lecture 25 1. Mapping Data Elements to Hypothesis
Lecture 26 2. Mapping Teams to Data Elements
Lecture 27 3. Framework CASED
Lecture 28 4. Data Pull and Clean
Lecture 29 5. Validating Hypothesis
Lecture 30 6. Summary
Lecture 31 7. Link Back to Business Problem
Lecture 0 1. What is a Predictive Algorithm
Lecture 0 2. Modelling Framework TESTS
Lecture 0 3. Target Variable Discovery
Lecture 0 4. Evaluation Metric
Lecture 0 5. Sampling
Lecture 0 6. Train your Model
Lecture 0 7. Score new population
Lecture 0 8. Summary
Lecture 0 9. Link back to business problem
Lecture 0 1. From Model to Strategy
Lecture 0 2. Dashboards
Lecture 0 3. Link back to Problem Statement
Lecture 0 1. Importance of Communication
Lecture 0 2. Pyramid Principle for Communication
Lecture 0 3. BONUS - Components of the Pyramid Principle (SCQA and MECE)
Lecture 0 4. Structured Email Writing
Lecture 0 5. Structured Note-Taking
Lecture 0 6. Introduction to Effective Presentations
Lecture 0 7. 6-Step Framework for Building Effective Presentations
Lecture 0 8. BONUS - SCQA Framework for Presentation Introductions
Lecture 0 9. Tips and Best Practices for Building Presentations
Lecture 0 10. The Art of Storytelling
Lecture 0 11. 3-Step Storytelling Framework
Lecture 0 12. Structured Thinking for Blogging
Any student who wants to learn