In this book, you will be trained hands-on with the most exciting cutting-edge technologies of computing – and, as you will see, with an easily adjustable blend of computer science and data science suitable for introductory courses in these and related fields. And you will program in Python – one of the most popular programming languages worldwide and the fastest-growing among them.

For more details, please read the Foreword:

• 538 hands-on, realistic examples of live code in snippets and case studies
• 471 exercises and assignments
• Immediate feedback with IPython, Jupyter Notebooks, and 557 Self-Assessment exercises
• Focused on Libraries: Use Python and data science libraries to accomplish significant tasks with minimal code
• Rich coverage of core principles: Problem solving, algorithm development, control statements, functions.
• Collections: Lists, tuples, dictionaries, sets, NumPy arrays, pandas Series & Dataframes
• 2D and 3D static, dynamic, and interactive visualizations
• Strings, text files, JSON serialization, CSV
• Procedural/function-style/object-oriented programming
• Data experiences with real-world datasets and data sources
• Introduction to Data Science modules: Basic statistics, simulation, graphics, random variables, data preprocessing, regression.
• Privacy, security, ethics, reproducibility, transparency.
• Case studies on AI, big data, and cloud data science: NLP, Twitter data mining, IBM Watson, machine learning, deep learning, computer vision, Hadoop, Spark, NoSQL, IoT.
• Open-source libraries: NumPy, pandas, Matplotlib, Seaborn, Folium, SciPy, NLTK, TextBlob, spaCy, Textatistic, Tweepy, scikit-learn, Keras, PubNub, etc.