Data Science & Business Analytics
Become a job-ready Data Scientist & Business Analyst with Python, statistics, SQL, data visualization, Power BI/Tableau, machine learning, and business intelligence. Turn raw data into insights and build real, portfolio-worthy analytics projects from data to decisions. Start free, go job-ready, and launch your career in data.
In short: This Data Science & Business Analytics program is a 60–65 hour, fully online, job-ready course. You start with 15 hours of free foundations (Python, statistics & probability, data handling, Git) and continue into a 45–50 hour paid program covering SQL, data cleaning and exploratory data analysis, data visualization with Power BI and Tableau, business analytics, machine learning, time series forecasting, and BI dashboards — finishing with a capstone analytics project, a portfolio, and full interview prep.
The Data Science & Business Analytics course is designed to help learners master the complete analytics workflow — from raw data to insights to data-driven decisions — and become immediately employable as Data Analysts, Business Analysts, and Data Scientists.
This course covers Python for data analysis, the essential statistics and probability behind analytics, SQL for querying databases, data cleaning and exploratory data analysis, data visualization and storytelling with Matplotlib, Seaborn, Power BI and Tableau, business analytics and statistical inference, machine learning for prediction, time series forecasting, and business intelligence dashboards. Learners build real, portfolio-worthy analytics projects at every stage using hands-on, project-based learning.
By completing this training, participants will be well-prepared for Data Analyst, Business Analyst, and Data Scientist roles, with a polished portfolio, a strong resume, and interview readiness.
Course Highlights
- End-to-end analytics coverage from Python foundations to business dashboards
- Hands-on SQL for querying and analyzing real databases
- Data cleaning and exploratory data analysis with Pandas
- Interactive dashboards with Power BI and Tableau
- Machine learning and time series forecasting for prediction
- Job-readiness: portfolio, resume, and interview prep
Learning Outcomes
- Analyze and visualize data with Python, NumPy, and Pandas
- Query and aggregate data from relational databases with SQL
- Clean, explore, and interpret real-world datasets
- Build interactive dashboards with Power BI and Tableau
- Apply machine learning and forecasting to business problems
- Communicate insights through data storytelling
Job Opportunities
- Data Scientist
- Data Analyst
- Business Analyst
- BI Engineer / Developer
- Analytics Consultant
- Machine Learning Analyst
What You'll Build (Portfolio Projects)
- A set of SQL analysis queries on a real business database
- An exploratory data analysis (EDA) report on a real-world dataset
- An interactive Power BI / Tableau business dashboard
- A predictive machine learning model and a sales forecast
- A deployed end-to-end capstone analytics project
Tools & Skills Covered
- Python, SQL, Pandas, NumPy
- Matplotlib, Seaborn, scikit-learn
- Power BI / Tableau, Git
Material Includes
- Class recordings
- Datasets & project starter files
- Certificate
Who Can Join
- IT & Commerce Graduates
- Aspiring Data & Business Analysts
- Career Switchers
Related Courses
Free Foundation — 15 Hours
Start learning for free. Build your core Python, statistics, and data foundations before advancing to the job-ready Data Science & Business Analytics program.
Estimated Time: 5 Hours
Learning Objectives:- Write and run Python programs confidently
- Use core programming logic to prepare for data analytics
- Python setup, syntax, variables, and data types
- Conditionals, loops, functions, and modules
- Lists, dictionaries, and file handling for data
- Build Python scripts that read, clean, and summarize data
Estimated Time: 4 Hours
Learning Objectives:- Understand the statistics that power data analysis
- Apply probability to reason about data and uncertainty
- Descriptive statistics: mean, median, variance, distributions
- Probability, sampling, and the normal distribution
- Correlation, hypothesis testing, and confidence intervals
- Compute statistics and visualize distributions in Python
Estimated Time: 4 Hours
Learning Objectives:- Manipulate numerical data efficiently with NumPy
- Load, clean, and transform datasets with Pandas
- NumPy arrays and vectorized operations
- Pandas Series, DataFrames, indexing, and grouping
- Handling missing data and merging datasets
- Clean and analyze a real CSV dataset with Pandas
Estimated Time: 2 Hours
Learning Objectives:- Track code and notebooks with Git
- Collaborate and showcase work on GitHub
- Repositories, commits, and branches
- Merging, pull requests, and conflict resolution
- Building a professional analytics GitHub profile
- Push your first notebooks and projects to GitHub
Paid Job-Ready Program — 45–50 Hours
Go from foundations to fully employable. Master SQL, data cleaning and exploratory analysis, data visualization, business analytics, machine learning, forecasting, and BI dashboards — everything you need to land your first data or business analyst job.
Estimated Time: 5 Hours
Learning Objectives:- Query and aggregate data from relational databases
- Answer business questions directly with SQL
- SELECT, WHERE, GROUP BY, and ORDER BY
- Joins, subqueries, and common table expressions
- Window functions and analytical aggregations
- Write SQL analysis queries on a real business database
Estimated Time: 5 Hours
Learning Objectives:- Turn raw, messy data into analysis-ready datasets
- Uncover patterns through exploratory data analysis
- Data cleaning, encoding, and outlier handling
- Feature scaling and transformation
- Exploratory data analysis (EDA) techniques
- Produce a full EDA report on a real-world dataset
Estimated Time: 5 Hours
Learning Objectives:- Communicate insights with clear visualizations
- Build interactive dashboards for business users
- Matplotlib and Seaborn plotting in Python
- Choosing the right chart for the message
- Interactive dashboards with Power BI and Tableau
- Build a visual data-story dashboard in Power BI or Tableau
Estimated Time: 4 Hours
Learning Objectives:- Apply statistical inference to business decisions
- Translate data findings into actionable recommendations
- Hypothesis testing and A/B testing for business
- Regression analysis and key business metrics (KPIs)
- Cohort, funnel, and customer segmentation analysis
- Run an A/B test analysis and interpret business impact
Estimated Time: 7 Hours
Learning Objectives:- Build classification and regression models
- Understand how core ML algorithms work
- Linear & logistic regression
- Decision trees, random forests, and gradient boosting
- Clustering, k-NN, and the scikit-learn workflow
- Train and compare predictive models on real data
Estimated Time: 5 Hours
Learning Objectives:- Measure and improve model performance
- Engineer features that boost accuracy
- Train/test splits, cross-validation, and metrics
- Bias-variance, overfitting, and regularization
- Hyperparameter tuning and feature engineering pipelines
- Tune and validate a model to production quality
Estimated Time: 4 Hours
Learning Objectives:- Analyze data that changes over time
- Forecast future business trends
- Trend, seasonality, and stationarity
- Moving averages and exponential smoothing
- ARIMA and modern forecasting techniques
- Build a sales forecasting model on time series data
Estimated Time: 4 Hours
Learning Objectives:- Understand how big data is stored and processed
- Work with modern cloud analytics tools
- Big data concepts, data lakes, and warehouses
- Distributed processing with Spark fundamentals
- Cloud analytics and data pipeline basics
- Query a large dataset with a cloud analytics tool
Estimated Time: 5 Hours
Learning Objectives:- Design executive-ready BI dashboards
- Tell a compelling story with data
- Dashboard design principles and KPI selection
- Building interactive reports in Power BI / Tableau
- Data storytelling and presenting to stakeholders
- Build and present an interactive BI dashboard
Estimated Time: 4 Hours
Learning Objectives:- Ship a complete, portfolio-ready analytics project
- Prepare for the data and business analyst job search
- End-to-end capstone analytics project planning and build
- Portfolio, GitHub, and resume optimization
- Analytics interview, case-study, and SQL prep
- Build and present an end-to-end capstone analytics project
- Mock interviews and resume review