Python is the go-to language for data science. Proficiency in Python libraries like NumPy, Pandas, Matplotlib, and Scikit-learn is essential. If you're familiar with other languages like R or Java, that's a plus, but focus on mastering Python for data science.

Brush up on core statistical concepts like hypothesis testing, regression analysis, and probability. Learn the fundamentals of machine learning algorithms like linear regression, decision trees, random forests, and classification methods. Brush up on core statistical concepts like hypothesis testing, regression analysis, and probability. Learn the fundamentals of machine learning algorithms like linear regression, decision trees, random forests, and classification methods.

Learn how to acquire data from various sources, handle missing values, and clean and manipulate data for analysis.

Being able to query databases to retrieve relevant data is a valuable skill for data scientists.


https://dqxeclau.top/download/ebooks/beginners-guide-data-science

I hope it helps!

Effective communication of insights is crucial. Master data visualization tools like Tableau, Power BI, or libraries like Seaborn and Matplotlib to create clear and impactful visualizations.