Course Content
Introduction to Data Science
0/3
Learning Objectives:
What is Data Science?
Data Science Lifecycle
Python for Data Science
0/7
Learning Objectives:
Introduction to Python
Functions and Modules
Data Structures in Python
Working with Libraries
Data Cleaning Techniques
Exploratory Data Analysis (EDA)
Data Visualization and Interpretation
0/4
Importance of Data Visualization
Data Visualization Techniques
Visualization Libraries and Tools
Best Practices for Visualization
Statistical Analysis for Data Science
0/4
Descriptive Statistics
Inferential Statistics
Hypothesis Testing
Correlation and Regression Analysis
Machine Learning Concepts
0/9
Overview of Machine Learning
Supervised Learning
Understanding Supervised Learning
Common Algorithms
Unsupervised Learning
Understanding Unsupervised Learning
Common Algorithms
Model Evaluation and Selection
Evaluating Model Performance
Advanced Machine Learning Techniques
0/4
Ensemble Learning Methods
Feature Engineering
Hyperparameter Tuning
Model Deployment
Introduction to Deep Learning
0/5
Introduction to Deep Learning
Neural Network Basics
Deep Learning Frameworks
Convolutional Neural Networks (CNN)
Recurrent Neural Networks (RNN)
Capstone Project
0/4
Project Planning
Data Preparation and Analysis
Modeling and Evaluation
Presentation of Results
Data Science and Analytics
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