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Data Science for Business Professionals


Become a Data Driven Decision Maker

Key Highlights

Course Length

2 Weeks (30+ Lessons)

100% Online

With Continuous Learning Community support + Monthly Live Webinars


4-5 Hours/Week

Learning Access

Resource Toolkit & Templates + Unlimited Networking Events

Fastest Way to Understand the nuances of Applied Data Science, ML and when and how to use it in real business scenarios. Highly recommend for every business professional (especially non technical folks!)
Sudha P
Project Manager, TCS
With real world examples & case studies the course gave me all tools, vocabulary and resources to effectively manage Data Science projects & better interlock with senior management teams as well discuss specifics with Data Science teams.
Sudha M
Data Analyst, Flipkart

What will you Learn?

Top skills you will learn

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 Curriculum

  •    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
  •    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
  •    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
  •    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
  •    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
  •    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
  •    Summary
  •    Final Exam

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.

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Still thinking?
If this is right for you

"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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