Data Science Contents with Java

📊 Data Science Contents (Java + OOP + DSA)

• 1. Core Java – Syntax, Loops, Arrays, Strings, Exception Handling
• 2. Object-Oriented Programming – Classes, Objects, Inheritance, Polymorphism, Encapsulation, Abstraction
• 3. Data Structures & Algorithms – Arrays, LinkedList, Stack, Queue, Trees, Graphs, HashMap, Searching, Sorting, Dynamic Programming
• 4. Mathematics & Statistics – Linear Algebra, Probability, Hypothesis Testing, Descriptive & Inferential Statistics
• 5. Data Handling in Java – JDBC, File Handling, Working with CSV/Excel, JSON/XML parsing
• 6. Data Science Libraries in Java – Weka, Deeplearning4j, Smile (Statistical Machine Intelligence Library)
• 7. Databases & SQL – MySQL, PostgreSQL, Joins, Aggregations, Window Functions
• 8. Data Cleaning & Preprocessing – Handling Missing Data, Normalization, Scaling, Outlier Detection
• 9. Data Visualization – JavaFX Charts, JFreeChart, Integration with BI Tools (Power BI, Tableau)
• 10. Machine Learning (with Java) – Regression, Classification, Clustering, Model Evaluation (using Weka/Smile)
• 11. Big Data & Advanced Tools – Hadoop, Spark (Java API), Kafka
• 12. Projects – Real-world case studies (Prediction Models, Sentiment Analysis, Recommendation System)