In the Python for Data Science and Machine Learning Bootcamp, you will:
- Gain a solid understanding of Python programming fundamentals and syntax.
- Learn how to use Python libraries such as NumPy, Pandas, and Matplotlib for data manipulation, analysis, and visualization.
- Explore the basics of statistics and probability theory to lay the foundation for data science.
- Understand the principles of machine learning and how to apply various algorithms using scikit-learn.
- Learn how to preprocess data, handle missing values, and perform feature engineering.
- Dive into supervised learning techniques such as linear regression, logistic regression, decision trees, and random forests.
- Discover unsupervised learning algorithms including clustering and dimensionality reduction.
- Gain knowledge of evaluation metrics and techniques for assessing model performance.
- Learn how to implement natural language processing (NLP) and sentiment analysis using Python.
- Apply your skills to real-world projects and datasets, putting your knowledge into practice.
By the end of this bootcamp, you will have a strong foundation in Python for data science and machine learning. You will be equipped with the skills to perform data analysis, build predictive models, and extract insights from complex datasets. Whether you’re a beginner or have some programming experience, this bootcamp will provide you with the tools and knowledge to embark on a career in data science and machine learning.
