Introduction to Data-Driven Decision Making
( 25 Modules )

Module #1
Introduction to Data-Driven Decision Making
Overview of the importance of data-driven decision making in business and everyday life

Module #2
Understanding Decision Making
Theories and models of decision making, including rational and intuitive approaches

Module #3
The Role of Data in Decision Making
How data can inform and improve decision making, with examples from various industries

Module #4
Data-Driven Decision Making Frameworks
Introducing frameworks and methodologies for data-driven decision making, such as CRISP-DM and Six Thinking Hats

Module #5
Data Sources and Collection Methods
Overview of data sources, including internal and external data, and data collection methods, such as surveys and sensors

Module #6
Data Quality and Preprocessing
Importance of data quality, data preprocessing techniques, and data cleaning methods

Module #7
Data Visualization Fundamentals
Introduction to data visualization principles, including types of charts and graphs, and best practices

Module #8
Descriptive Statistics and Data Summarization
Calculating summary statistics, understanding distributions, and data summarization techniques

Module #9
Exploratory Data Analysis (EDA)
Using EDA to uncover patterns, relationships, and insights in data

Module #10
Inferential Statistics and Hypothesis Testing
Introduction to inferential statistics, hypothesis testing, and confidence intervals

Module #11
Regression Analysis
Understanding simple and multiple regression, including model interpretation and limitations

Module #12
Decision Trees and Random Forests
Introduction to decision trees, random forests, and ensemble methods for classification and regression

Module #13
Cluster Analysis and Segmentation
K-means clustering, hierarchical clustering, and segmentation techniques for customer and market analysis

Module #14
Text Analytics and Sentiment Analysis
Introduction to text analytics, sentiment analysis, and natural language processing

Module #15
Communicating Data Insights
Effective communication of data insights, including storytelling and presentation techniques

Module #16
Case Studies in Data-Driven Decision Making
Real-world examples of data-driven decision making in various industries, including healthcare, finance, and marketing

Module #17
Ethics in Data-Driven Decision Making
The importance of ethics in data-driven decision making, including bias, privacy, and transparency

Module #18
Data-Driven Decision Making in Practice
Applying data-driven decision making in real-world scenarios, including A/B testing and experimentation

Module #19
Working with Stakeholders and Teams
Collaboration and stakeholder management in data-driven decision making projects

Module #20
Data Governance and Management
Data governance frameworks, data management best practices, and data quality control

Module #21
Big Data and NoSQL Databases
Introduction to big data, NoSQL databases, and distributed computing systems

Module #22
Machine Learning and AI in Decision Making
Introduction to machine learning and AI in decision making, including supervised and unsupervised learning

Module #23
Predictive Modeling and Forecasting
Building predictive models, including time series forecasting and regression analysis

Module #24
Implementing Data-Driven Decision Making in Organizations
Strategies for implementing data-driven decision making in organizations, including change management and cultural transformation

Module #25
Course Wrap-Up & Conclusion
Planning next steps in Introduction to Data-Driven Decision Making career

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Introduction to Data-Driven Decision Making ( 25 Modules )

Introduction to Data-Driven Decision Making
( 25 Modules )