Data Science and Analytics
Master data analysis, visualization, and predictive modeling with industry-relevant curriculum and hands-on projects.
This program is offered in partnership with
Program Overview
Transform data into actionable insights with our comprehensive Data Science and Analytics program. Learn to collect, analyze, and visualize data using industry-standard tools and techniques. This program is perfect for professionals looking to enter the data science field or enhance their analytical skills. The curriculum covers everything from data fundamentals to advanced analytics and big data processing.
Program Details
12-18 months
Online
Beginner to Intermediate
What You'll Learn
- Master data collection, cleaning, and preprocessing techniques
- Perform statistical analysis and hypothesis testing
- Create compelling data visualizations and interactive dashboards
- Build predictive models using machine learning algorithms
- Work with big data tools and cloud platforms
- Communicate data insights effectively to stakeholders
- Apply data science techniques to solve real-world business problems
Curriculum
Data Science Fundamentals
- Data Science Lifecycle
- Python & R Basics
- Data Types & Structures
- Jupyter Notebooks
Data Collection & Cleaning
- Web Scraping
- APIs & Data Sources
- Data Cleaning Techniques
- ETL Processes
Exploratory Data Analysis
- Statistical Analysis
- Data Visualization
- Pattern Recognition
- Correlation Analysis
Statistical Modeling
- Hypothesis Testing
- Regression Analysis
- Time Series Analysis
- Statistical Inference
Machine Learning for Data Science
- Supervised Learning Algorithms
- Unsupervised Learning
- Model Selection & Tuning
- Cross-Validation
Big Data & Cloud Computing
- Hadoop Ecosystem
- Apache Spark
- Cloud Platforms (AWS, Azure)
- Distributed Computing
Data Visualization & Storytelling
- Tableau
- Power BI
- Dashboard Design
- Data Storytelling Techniques
Advanced Analytics
- Predictive Analytics
- Prescriptive Analytics
- A/B Testing
- Experimental Design
Data Engineering
- Data Pipelines
- Data Warehousing
- Data Lakes
- ETL/ELT Processes
Capstone Project
- End-to-End Data Science Project
- Portfolio Development
- Industry Case Study
Prerequisites
Basic mathematics and statistics knowledge, familiarity with Excel or spreadsheet software. Programming experience is beneficial but not required.