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Data Science - Coggle Diagram
Data Science
Introduction to Data Science
1.1. Definition of Data Science
1.2. Importance of Data Science
1.3. Overview of Data Science Tools and Techniques
Basic Programming Concepts
2.1. Introduction to Python
2.1.1. Installing and Setting Up Python
2.1.2. Basic Python Syntax
2.1.3. Object-Oriented Programming Concepts
2.2. Variables and Data Types
2.2.1. Numeric Data Types
2.2.2. Strings
2.2.3. Lists, Tuples, and Dictionaries
2.3. Operators and Expressions
2.3.1. Arithmetic Operators
2.3.2. Comparison Operators
2.3.3. Logical Operators
2.4. Control Structures
2.4.1. Conditional Statements
2.4.2. Loops
2.5. Functions and Modules
2.5.1. Defining and Calling Functions
2.5.2. Creating and Importing Modules
Data Manipulation and Analysis
3.1. Introduction to Pandas
3.1.1. Series and DataFrames
3.1.2. Indexing and Selecting Data
3.1.3. Data Cleaning and Preprocessing
3.2. Data Aggregation and Grouping
3.2.1. GroupBy Operations
3.2.2. Pivot Tables
3.3. Data Visualization
3.3.1. Matplotlib Basics
3.3.2. Seaborn for Statistical Visualization
Machine Learning Fundamentals
4.1. Introduction to Machine Learning
4.1.1. Supervised vs. Unsupervised Learning
4.1.2. Regression vs. Classification
4.2. Model Selection and Evaluation
4.2.1. Cross-Validation
4.2.2. Model Performance Metrics
4.3. Linear Regression
4.3.1. Simple Linear Regression
4.3.2. Multiple Linear Regression
4.4. Classification Algorithms
4.4.1. Logistic Regression
4.4.2. Decision Trees
4.4.3. Random Forests
4.5. Clustering Algorithms
4.5.1. K-Means Clustering
4.5.2. Hierarchical Clustering
Data Modeling and Evaluation
5.1. Model Selection and Validation
5.1.1. Train-Test Split
5.1.2. K-Fold Cross Validation
5.2. Model Building
5.2.1. Choosing the Right Model
5.2.2. Tuning Model Parameters
5.3. Model Evaluation and Optimization
5.3.1. Model Performance Metrics
5.3.2. Bias-Variance Tradeoff
5.4. Presentation and Communication of Results
5.4.1. Creating Reports and Presentations
5.4.2. Communicating Results to Stakeholders
5.5. Deployment and Maintenance of Data Science Applications
5.5.1. Deploy