Overview
Unlock Advanced Statistical Techniques for Data Science and Business Analysis
Syllabus
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- Introduction to Data Science
-- Overview of Data Science and its importance in business
-- Key roles and skills in Data Science
- Data Collection and Management
-- Types of data: structured vs. unstructured
-- Data collection techniques and sources
-- Data cleaning and preprocessing
- Exploratory Data Analysis (EDA)
-- Descriptive statistics
-- Data visualization techniques
-- Identifying patterns and outliers in data
- Introduction to Machine Learning
-- Supervised vs. unsupervised learning
-- Common algorithms: linear regression, decision trees, clustering
-- Evaluation and validation of models
- Applying Machine Learning to Business
-- Case studies of Machine Learning in business contexts
-- Solving business challenges with predictive models
-- Model deployment and maintenance
- Business Analytics
-- Key performance indicators and metrics
-- Dashboard creation and data storytelling
-- Scenario analysis and decision-making support
- Data-Driven Decision Making
-- Creating data-driven business strategies
-- Communicating data insights to stakeholders
-- Ethical considerations in data usage
- Tools and Technologies in Data Science
-- Overview of popular data science tools: Python, R, SQL
-- Introduction to software platforms for business analytics (e.g., Tableau, Power BI)
- Capstone Project
-- Real-world business data set analysis
-- Problem-solving using data science techniques
-- Presentation and interpretation of results to a business audience
Taught by
Tags
On-Demand
