Overview
Learn the data analysis skills you need to succeed in different and advancing industries, both today and tomorrow.
Syllabus
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- Introduction to Data Analysis
-- Understanding Data: Types and Sources
-- Basic Tools and Software for Data Analysis
- Fundamental Skills in Data Analysis
-- Data Cleaning and Preparation
-- Exploratory Data Analysis (EDA)
-- Statistical Concepts and Methods
-- Data Visualization Techniques
- Industry-Specific Data Considerations
-- Data Analysis in Retail
--- Consumer Behavior and Sales Forecasting
--- Inventory Management Analytics
-- Data Analysis in Healthcare
--- Patient Data Management and Privacy
--- Epidemiological Data Analysis
-- Data Analysis in Finance
--- Risk Analysis and Management
--- Fraud Detection and Prevention
- Advanced Data Analysis Techniques
-- Machine Learning and Predictive Analytics
-- Big Data and Real-Time Analysis
-- Data Mining and Text Analytics
- Practical Applications and Case Studies
-- Analyzing Industry-Specific Case Studies
-- Hands-on Projects with Real-World Data Sets
- Tools and Software for Data Analysis
-- Overview of Popular Data Analysis Software (e.g., Python, R, Excel)
-- Introduction to Data Analysis Libraries and Frameworks
--- Pandas, NumPy, and SciPy
--- Machine Learning Libraries: Scikit-Learn, TensorFlow
- Ethical Considerations and Data Governance
-- Privacy Concerns and Data Protection Policies
-- Ensuring Data Accuracy and Integrity
- Future Trends in Data Analysis
-- The Impact of Automation and AI
-- Emerging Technologies and Their Implications
Taught by
Tags
On-Demand
