Data Science for Business Professionals
$99
4.5 (1725)
Rated 4.5 out of 5
Duration
2 Weeks (30+ Lessons) at 4-5 Hours/Week
Data Science for Business Professionals
Manage Data Science Projects & Teams to Build Business Impact Without Programming or Statistics
Become a Data Driven Decision Maker
Course Length
2 Weeks (30+ Lessons)
Effort
4-5 Hours/Week
100% Online
With Continuous Learning Community support + Monthly Live Webinars
Learning Access
Resource Toolkit & Templates + Unlimited Networking Events
What will you Learn?
- A complete data science online course to demonstrate a fundamental understanding of end-to-end aspects of Data Science and the ability to interlock with the Management team and Data Scientist team.
- Types of Data Science Models & Algorithms commonly used in the industry along with is business applications.
- Data science training online to help you work effectively with data science teams to build great products & services.
- Ability to jumpstart a career as a Data Smart Manager.
Key Topics Covered
Data Analysis to Drive Decision Making, Analysis Methods – Descriptive Analysis, Predictive Analysis, Prescriptive Analysis. Big Data Terminologies, Data Science Algorithms and its applications (ex. Component Analysis, K-Means Clustering, Association Rules, Regression Analysis, K-Nearest Neighbors, Decision Trees etc). Unsupervised Learning, Data Visualization, Data Story Telling, Data Monetization. Setting up and Managing Data Teams and more..
Course Content
Setting the context
Setting the context
Learning Objectives
Course Overview
Learning Objectives
Course Overview
Chapter 1: Understanding Data Science
Learning Objective
1.1: What is Data Science?
1.2: What are “Data Science enabled Products”?
1.3: Big Data Landscape
1.4: Data Science Basics & Machine Learning
Chapter Quiz
1.1: What is Data Science?
1.2: What are “Data Science enabled Products”?
1.3: Big Data Landscape
1.4: Data Science Basics & Machine Learning
Chapter Quiz
Chapter 2: Data Science Algorithms and Analysis Methods
Learning Objective
2.1: Analysis Methods
2.2: Descriptive Analysis
2.3: Predictive Analysis & Prescriptive Analysis
2.4: Big Data Terminologies
2.5: Data Science Algorithms
2.6: Principal Component Analysis
2.7: K-Means Clustering
2.8: Association Rules
2.9: Page Rank Algorithm
2.10: Regression Analysis
2.11: K-Nearest Neighbors
2.12: Decision Trees
Unsupervised Learning
2.1: Analysis Methods
2.2: Descriptive Analysis
2.3: Predictive Analysis & Prescriptive Analysis
2.4: Big Data Terminologies
2.5: Data Science Algorithms
2.6: Principal Component Analysis
2.7: K-Means Clustering
2.8: Association Rules
2.9: Page Rank Algorithm
2.10: Regression Analysis
2.11: K-Nearest Neighbors
2.12: Decision Trees
Unsupervised Learning
Chapter 3: Building Products With Data Science
Learning Objective
3.1: Data Science Project
3.2: Data Format
3.3: Variable Types
3.4: Variable Selection
3.5: Feature Engineering
3.6: Algorithm Selection
3.7: Parameter Tuning
3.8: Evaluating Results
3.9: Building Products
3.10: Invisible AI As The Best AI
3.11: Actionable Insights
3.12: Your Users Are Not Data Scientists
3.13: Design is AI’s Best Friend
3.14: Managers Deserve Less
3.15: Don’t Visualize Data
3.16: Be The QA You Want To See
3.17: Ask Your Users: Back Testing
3.18: Data Science Pitfalls
Unsupervised Learning
3.1: Data Science Project
3.2: Data Format
3.3: Variable Types
3.4: Variable Selection
3.5: Feature Engineering
3.6: Algorithm Selection
3.7: Parameter Tuning
3.8: Evaluating Results
3.9: Building Products
3.10: Invisible AI As The Best AI
3.11: Actionable Insights
3.12: Your Users Are Not Data Scientists
3.13: Design is AI’s Best Friend
3.14: Managers Deserve Less
3.15: Don’t Visualize Data
3.16: Be The QA You Want To See
3.17: Ask Your Users: Back Testing
3.18: Data Science Pitfalls
Unsupervised Learning
Chapter 4: Engaging With Data Science Teams
Learning Objective
4.1: PMs Should Engage With Data Scientists
4.2: Product Marketing & Data Science
4.3: What Is A Data Smart Product Manager?
4.4: Personas In The Data Science Arena
Chapter Quiz
4.1: PMs Should Engage With Data Scientists
4.2: Product Marketing & Data Science
4.3: What Is A Data Smart Product Manager?
4.4: Personas In The Data Science Arena
Chapter Quiz
Chapter 5: Getting Started With Essentials Of Data Science
Learning Objective
5.1: Data Science Essentials
5.2: Linear Regression
5.3: Scatter Plot
5.4: Regression Equation
5.5: Regression Result
5.6: Regression & Data Science
5.7: Cluster Analysis
Chapter Quiz
5.1: Data Science Essentials
5.2: Linear Regression
5.3: Scatter Plot
5.4: Regression Equation
5.5: Regression Result
5.6: Regression & Data Science
5.7: Cluster Analysis
Chapter Quiz
Chapter 6: Data Strategy and Visualization
Learning Objective
6.1: What Is Data Strategy?
6.2: What Are Some Examples Of Divergent Strategies?
6.3: Data Visualization
6.4: Time Series Data
6.5: Cartographic Data
6.6: Financial Chart
6.7: Interactive Visualization
6.8: Heat Maps
6.9: Visualizing Scale
6.10: Music
6.11: Five ThirtyEight Visualization
Chapter Quiz
6.1: What Is Data Strategy?
6.2: What Are Some Examples Of Divergent Strategies?
6.3: Data Visualization
6.4: Time Series Data
6.5: Cartographic Data
6.6: Financial Chart
6.7: Interactive Visualization
6.8: Heat Maps
6.9: Visualizing Scale
6.10: Music
6.11: Five ThirtyEight Visualization
Chapter Quiz
Conclusion
Summary
Final Exam
Final Exam
What Learners Say About Our Program
Ideal For
Business Professionals like Business Analysts, Project Managers, Program Managers.
Technology Professionals like – Q/A, Engineering Leads, Solutions Architect, Software Developers.
Customer Facing Professionals like – Marketing Analysts, Sales, Entrepreneurs, Delivery Managers, Functional Managers.
Anyone who wants to build and end to end understanding and orientation of the world of Data Science and how to drive Data Science projects & Data Driven business decisions.
NO prior knowledge of Data Science, Programming or Statistics required.
Business Professionals like Business Analysts, Project Managers, Program Managers.
Technology Professionals like – Q/A, Engineering Leads, Solutions Architect, Software Developers.
Preparing you for Global Certification
Get an Industry accepted Data Science for Business Professionals certification from IPL that enhances your professional equity and bolsters your career profile.
Customer Facing Professionals like – Marketing Analysts, Sales, Entrepreneurs, Delivery Managers, Functional Managers.
Anyone who wants to build and end to end understanding and orientation of the world of Data Science and how to drive Data Science projects & Data Driven business decisions.
NO prior knowledge of Data Science, Programming or Statistics required.
Common Scenarios to Enroll
"Industry wants to hire professionals who not only understand the depth of data science but can leverage that to business outcomes."
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