- Fundamentals of Data Science: Understand the role of a data scientist, key concepts, and the data science process.
- Python Programming for Data Science: Master Python programming and its libraries for data manipulation, analysis, and visualization.
- Data Collection and Preprocessing: Learn how to collect, clean, and preprocess data for further analysis using various techniques.
- Exploratory Data Analysis (EDA): Understand how to analyze and summarize data using descriptive statistics, data distribution, and correlation analysis.
- Statistical Analysis: Develop skills in probability theory, hypothesis testing, regression analysis, and other statistical concepts.
- Machine Learning Fundamentals: Learn about supervised and unsupervised learning, common machine learning algorithms, and model evaluation techniques.
- Supervised and Unsupervised Learning Techniques: Master regression, classification, clustering, and dimensionality reduction techniques.