The Decision Maker’s Guide to Data Science: A Complete Mastery Programme
Introduction
In a world where data fuels every competitive edge, decision makers must know how to translate complex information into clear strategies. This intensive programme equips leaders and professionals with practical data science skills tailored to business contexts. Participants will learn to harness data, build predictive models, and use visualization to uncover insights that drive smarter decisions and sustainable results.
Objectives
By the end of this programme, participants will be able to:
* Grasp the **data science lifecycle** and its role in business success.
* Apply **statistical and machine learning models** to solve organizational challenges.
* Utilize **Python and modern data tools** for analysis and visualization.
* Communicate insights effectively with **data storytelling techniques**.
* Leverage **predictive analytics** to guide strategic and operational decisions.
Methodology
The programme combines:
* **Expert-led lectures** to explain key concepts.
* **Hands-on labs** with Python, Matplotlib, and Seaborn.
* **Real-world case studies** highlighting business applications.
* **Collaborative workshops** for team problem-solving.
* **Capstone projects** simulating practical organizational challenges.
Who Should Attend
This programme is designed for:
* Senior executives and decision makers seeking **data-driven leadership**.
* HR, finance, marketing, and operations professionals needing **data insight skills**.
* Business analysts and managers who want to **apply predictive analytics**.
* Professionals with little technical background who wish to **bridge the gap between data and business**.
Course Contents
Day 1: Introduction to Data Science and Analytics
* The role of data science in business.
* Overview of the data science lifecycle.
* Data types, structures, and exploratory analysis.
* Getting started with Python for business analytics.
Day 2: Data Handling and Visualization
* Data cleaning and preprocessing essentials.
* Addressing missing values and outliers.
* Visualizing trends with Matplotlib and Seaborn.
* Storytelling with data: transforming numbers into narratives.
* Practical visualization workshop.
Day 3: Statistics and Predictive Modeling
* Core statistics for decision makers.
* Correlation and regression for insight.
* Supervised learning models explained simply.
* Building and evaluating predictive models.
* Case-based application in business scenarios.
Day 4: Machine Learning Essentials
* Classification vs. regression models in practice.
* Decision trees, k-nearest neighbors, and support vector machines.
* Cross-validation for reliable results.
* Model tuning and feature selection.
* Translating machine learning outcomes into business impact.
Day 5: Capstone Project and Strategic Applications
* Designing an end-to-end data science project.
* Embedding insights into decision-making.
* Automating reporting and analysis pipelines.
* Best practices for organizational adoption of data science.
* Final project presentations and feedback.
Benefits
* Build **practical skills** to use data as a decision-making tool.
* Develop the ability to **translate analytics into actionable business insights**.
* Confidently apply **predictive and machine learning models** to strategy.
* Strengthen collaboration with technical and analytics teams.
* Walk away with a **capstone project** demonstrating applied mastery.
Enquiries and Registration
Enquiry at : admin@keleaders.com
Whatsapp: 0044 790 125 9494
For more details visit our website : www.keleaders.com
