📊 Data Science & Analytics (30+ Courses)
Data Science & Analytics focuses on turning raw data into valuable insights. Learn to collect, clean, and analyze data, apply statistical methods, and use modern tools for visualization and prediction. With 30+ courses, explore applications in business, healthcare, finance, and technology to make smarter, data-driven decisions.
- 10 Lessons
- 6 Studenst
Data Science with Python
Master data cleaning, analysis, visualization, and machine learning using Python libraries like Pandas, NumPy, Matplotlib, and Scikit-learn.
- 10 Lessons
- 6 Studenst
Data Analytics using Excel
Learn how to transform raw data into actionable insights using formulas, pivot tables, dashboards, and statistical tools in Excel.
- 10 Lessons
- 6 Studenst
Statistics for Data Science
Understand core statistical concepts like probability, distributions, hypothesis testing, and regression — the backbone of data modeling.
- 10 Lessons
- 6 Studenst
SQL for Data Analysis
Learn to query and manipulate databases efficiently using SQL — essential for data
analysts and business intelligence roles.
- 10 Lessons
- 6 Studenst
Exploratory Data Analysis (EDA)
Practice techniques for discovering trends, patterns, and anomalies in datasets through visual and statistical exploration.
- 10 Lessons
- 6 Studenst
Data Wrangling with Pandas
Prepare messy data for analysis by cleaning, transforming, reshaping, and filtering it using Python’s powerful Pandas library.
- 10 Lessons
- 6 Studenst
Data Visualization with Tableau
Create interactive dashboards and meaningful visual stories using drag-and-drop tools in Tableau for business intelligence reporting.
- 10 Lessons
- 6 Studenst
Data Visualization with Power BI
Build real-time dashboards and business reports using Microsoft Power BI — widely
used in enterprises for data-driven decision-making.
- 10 Lessons
- 6 Studenst
Business Intelligence & Analytics
Learn the full lifecycle of business analysis — from data extraction to insight delivery — using real-world enterprise case studies.
- 10 Lessons
- 6 Studenst
Time Series Forecasting
Predict future trends using statistical models (ARIMA, Exponential Smoothing) and deep learning (LSTM) for applications in finance and retail.
- 10 Lessons
- 6 Studenst
Predictive Analytics
Use data and statistical algorithms to predict future outcomes, trends, or behaviors — from customer churn to sales forecasts.
- 10 Lessons
- 6 Studenst
Big Data Fundamentals (Hadoop & HDFS)
Learn to process and store vast datasets using Hadoop Distributed File System
(HDFS), MapReduce, and Hive
- 10 Lessons
- 6 Studenst
Apache Spark for Data Processing
Process large-scale data in memory using Spark — ideal for fast, scalable big data
analytics in Python, Java, or Scala.
- 10 Lessons
- 6 Studenst
Feature Engineering for Machine Learning
Learn how to transform raw data into high-quality input features to boost model
performance and accuracy.
- 10 Lessons
- 6 Studenst
Dimensionality Reduction (PCA & t-SNE)
Reduce data complexity while retaining critical information — useful in high-dimensional datasets like image and genomic data.
- 10 Lessons
- 6 Studenst
Data Mining Techniques
Extract hidden patterns, trends, and knowledge from massive datasets using clustering, association rules, and decision trees.
- 10 Lessons
- 6 Studenst
Sentiment Analysis with Twitter Data
Analyze opinions and trends from social media posts using text mining, NLP, and
visualization techniques
- 10 Lessons
- 6 Studenst
Dimensionality Reduction (PCA & t-SNE)
Learn to process, analyze, and derive meaning from text data using tokenization,
stemming, named entity recognition, and more.
- 10 Lessons
- 6 Studenst
Data Storytelling & Presentation Skills
Combine analysis with narrative techniques to communicate insights clearly and
persuasively using charts, infographics, and summaries.
- 10 Lessons
- 6 Studenst
Real-Time Data Analysis
Learn tools like Apache Kafka and Spark Streaming to process data as it arrives —
essential in fraud detection and live monitoring.
- 10 Lessons
- 6 Studenst
Customer & Market Segmentation
Use clustering and unsupervised learning to group users or products based on
behavior, purchase history, or demographics.
- 10 Lessons
- 6 Studenst
Churn Prediction Modeling
Predict which customers are likely to leave and design strategies to retain them using
logistic regression and decision trees
- 10 Lessons
- 6 Studenst
Data Ethics & Governance
Understand data privacy, consent, bias, and responsible use of data in organizations under global regulations like GDPR.
- 10 Lessons
- 6 Studenst
ETL (Extract, Transform, Load) Process Mastery
Learn how to pull data from multiple sources, clean it, and load it into storage systems for analysis.
- 10 Lessons
- 6 Studenst
Data Warehousing & Star Schema Design
Design scalable data warehouses using facts and dimensions to support analytics and reporting in large organizations.
- 10 Lessons
- 6 Studenst
Google Data Studio for Reporting
Create visually appealing, dynamic dashboards integrated with Google Sheets,
Analytics, Ads, and more.
- 10 Lessons
- 6 Studenst
Financial Data Analytics
Analyze financial datasets using Python, Excel, or R to uncover trends in revenue,
profit, budgeting, and investment decisions
- 10 Lessons
- 6 Studenst
Healthcare Data Analytics
Study clinical and patient data to improve outcomes, reduce costs, and support medical research using analytical tools.
- 10 Lessons
- 6 Studenst
Marketing Analytics
Analyze campaign performance, ROI, customer behavior, and funnel efficiency to drive growth with data.
- 10 Lessons
- 6 Studenst
Data Science Capstone Project
Work on a real-world dataset — from data cleaning to deployment — showcasing your
complete end-to-end data science skills.
