Data Science Real-Life Data Science Exercises Included: Comprehensive guide to data science with practical exercises
Learn Data Science by Doing - Real-World Projects, Practical Exercises, and Essential Theory
Ready to go beyond the buzzwords and actually apply data science in real-world settings? This hands-on guide is your gateway to mastering the tools, concepts, and mindset of a professional data scientist - even if you're just starting out.
From data wrangling and exploratory analysis to machine learning and model evaluation, this book offers a complete roadmap - plus practical exercises and real datasets to help you solidify your understanding through action.
What You'll Learn:
✅ Foundations of data science and the data lifecycle
✅ Data collection, cleaning, and preprocessing techniques
✅ Exploratory data analysis (EDA) using Pandas, NumPy, and Matplotlib
✅ Feature engineering and selection
✅ Supervised and unsupervised machine learning models
✅ Real-world exercises using classification, regression, clustering
✅ Model evaluation, tuning, and deployment basics
✅ Python-based workflows with Scikit-learn, Jupyter, and more
✅ Working with real datasets: sales data, customer data, medical records, and more
✅ Tips for building a data science portfolio for interviews and freelancing
Whether you're transitioning into data science, studying for interviews, or looking to strengthen your practical skills - this book ensures you learn by doing, not just reading.
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