Courses
Data Management & Analytics Course
This course equips students with essential skills in handling, organizing, and analyzing data to drive informed decision-making. Covering database management, statistical methods, visualization techniques, and advanced analytics tools, it prepares learners for extracting insights from complex datasets in various industries through practical projects and real-world applications.
About Course
Career Prospects
- Data Analyst
- Data Scientist
- Business Intelligence Analyst
- Data Engineer
- Database Administrator
- Analytics Manager
- Big Data Specialist
- Data Architect
- Machine Learning Engineer
- Predictive Analyst
Course Curriculum
Module 1: Introduction to Data Management and Analytics
- Data Lifecycle Overview
- Types of Data Sources
- Data Governance Principles
- Ethical Considerations
- Industry Applications
Module 2: Database Fundamentals
- Relational Database Concepts
- Database Design and Normalization
- SQL Basics
- NoSQL Databases
- Data Modeling Techniques
Module 3: Data Cleaning and Preparation
- Data Quality Assessment
- Handling Missing Values
- Data Transformation Methods
- Outlier Detection
- Integration from Multiple Sources
Module 4: Statistical Foundations
- Descriptive Statistics
- Probability Distributions
- Hypothesis Testing
- Regression Analysis
- Correlation and Causation
Module 5: Data Visualization
- Visualization Principles
- Chart Types and Best Practices
- Dashboard Design
- Storytelling with Data
- Interactive Visuals
Module 6: SQL for Analytics
- Advanced SQL Queries
- Joins and Subqueries
- Aggregation Functions
- Window Functions
- Performance Optimization
Module 7: Programming for Data Analytics
- Python Basics for Data
- Libraries like Pandas and NumPy
- R Programming Fundamentals
- Data Manipulation in R
- Scripting Automation
Module 8: Big Data Technologies
- Introduction to Big Data
- Hadoop Ecosystem
- Apache Spark Basics
- Data Warehousing
- Cloud Data Platforms
Module 9: Advanced Analytics and Machine Learning
- Predictive Modeling
- Clustering Techniques
- Classification Algorithms
- Time Series Analysis
- Model Evaluation
Module 10: Projects, Ethics, and Career Development
- Capstone Projects
- Data Privacy Regulations
- Bias in Analytics
- Portfolio Building
- Job Search Strategies
Skills and Tools Covered
- Microsoft Excel
- SQL
- Python
- R
- Tableau
- Power BI
- Hadoop
- Apache Spark
- MySQL
- MongoDB
- Pandas
- NumPy
- KNIME
- RapidMiner
- Google Analytics
- IBM InfoSphere
- Talen
- Splunk
Duration
- 3 Months
Cost
- KES. 45,000