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For introductory-level Python programming and/or data-science courses.
A groundbreaking, flexible approach to computer science and data science
The Deitels' Introduction to Python for Computer Science and Data Science: Learning to Program with AI, Big Data and the Cloud offers a unique approach to teaching introductory Python programming, appropriate for both computer-science and data-science audiences. Providing the most current coverage of topics and applications, the book is paired with extensive traditional supplements as well as Jupyter Notebooks supplements. Real-world datasets and artificial-intelligence technologies allow students to work on projects making a difference in business, industry, government and academia. Hundreds of examples, exercises, projects (EEPs) and implementation case studies give students an engaging, challenging and entertaining introduction to Python programming and hands-on data science.
The book's modular architecture enables instructors to conveniently adapt the text to a wide range of computer-science and data-science courses offered to audiences drawn from many majors. Computer-science instructors can integrate as much or as little data-science and artificial-intelligence topics as they'd like, and data-science instructors can integrate as much or as little Python as they'd like. The book aligns with the latest ACM/IEEE CS-and-related computing curriculum initiatives and with the Data Science Undergraduate Curriculum Proposal sponsored by the National Science Foundation.
For introductory-level Python programming and/or data-science courses.
A groundbreaking, flexible approach to computer science and data science
The Deitels' Introduction to Python for Computer Science and Data Science: Learning to Program with AI, Big Data and the Cloud offers a unique approach to teaching introductory Python programming, appropriate for both computer-science and data-science audiences. Providing the most current coverage of topics and applications, the book is paired with extensive traditional supplements as well as Jupyter Notebooks supplements. Real-world datasets and artificial-intelligence technologies allow students to work on projects making a difference in business, industry, government and academia. Hundreds of examples, exercises, projects (EEPs) and implementation case studies give students an engaging, challenging and entertaining introduction to Python programming and hands-on data science.
The book's modular architecture enables instructors to conveniently adapt the text to a wide range of computer-science and data-science courses offered to audiences drawn from many majors. Computer-science instructors can integrate as much or as little data-science and artificial-intelligence topics as they'd like, and data-science instructors can integrate as much or as little Python as they'd like. The book aligns with the latest ACM/IEEE CS-and-related computing curriculum initiatives and with the Data Science Undergraduate Curriculum Proposal sponsored by the National Science Foundation.
Paul J. Deitel, CEO and Chief Technical Officer of Deitel & Associates, Inc., is an MIT graduate with 38 years of computing and corporate training experience and is an Oracle® Java® Champion and a Microsoft® C# MVP (2012-2014). He is a best-selling programming-language textbook/professional book/video/e-learning author. Paul is one of the world's most experienced programming-languages trainers. Through Deitel & Associates, Inc., he has delivered hundreds of programming courses worldwide to clients, including Cisco, IBM, Siemens, Sun Microsystems (now Oracle), Dell, Fidelity, NASA at the Kennedy Space Center, the National Severe Storm Laboratory, White Sands Missile Range, Rogue Wave Software, Boeing, SunGard Higher Education, Nortel Networks, Puma, iRobot, Invensys and many more. He and his co-author, Dr. Harvey M. Deitel, are the world's best-selling programming-language textbook/professional book/video authors.
Dr. Harvey M. Deitel, Chairman and Chief Strategy Officer of Deitel & Associates, Inc., has over 55 years of experience in computing. Dr. Deitel earned B.S. and M.S. degrees in Electrical Engineering from MIT and a Ph.D. in Mathematics from Boston University-he studied computing in each of these programs just before they spun off Computer Science programs. He has extensive college teaching experience, including earning tenure and serving as the Chairman of the Computer Science Department at Boston College before founding Deitel & Associates, Inc., in 1991 with his son, Paul. The Deitels' publications have earned international recognition, with more than 100 translations published in Japanese, German, Russian, Spanish, French, Polish, Italian, Simplified Chinese, Traditional Chinese, Korean, Portuguese, Greek, Urdu and Turkish. Dr. Deitel has delivered hundreds of programming courses to academic, corporate, government and military clients.
- PART 1
- CS: Python Fundamentals Quickstart
- CS 1. Introduction to Computers and Python
- DS Intro: AI-at the Intersection of CS and DS
- CS 2. Introduction to Python Programming
- DS Intro: Basic Descriptive Stats
- CS 3. Control Statements and Program Development
- DS Intro: Measures of Central Tendency-Mean, Median, Mode
- CS 4. Functions
- DS Intro: Basic Statistics- Measures of Dispersion
- CS 5. Lists and Tuples
- DS Intro: Simulation and Static Visualization
- PART 2
- CS: Python Data Structures, Strings and Files
- CS 6. Dictionaries and Sets
- DS Intro: Simulation and Dynamic Visualization
- CS 7. Array-Oriented Programming with NumPy, High-Performance NumPy Arrays
- DS Intro: Pandas Series and DataFrames
- CS 8. Strings: A Deeper Look Includes Regular Expressions
- DS Intro: Pandas, Regular Expressions and Data Wrangling
- CS 9. Files and Exceptions
- DS Intro: Loading Datasets from CSV Files into Pandas DataFrames
- PART 3
- CS: Python High-End Topics
- CS 10. Object-Oriented Programming
- DS Intro: Time Series and Simple Linear Regression
- CS 11. Computer Science Thinking: Recursion, Searching, Sorting and Big O
- CS and DS Other Topics Blog
- PART 4
- AI, Big Data and Cloud Case Studies
- DS 12. Natural Language Processing (NLP), Web Scraping in the Exercises
- DS 13. Data Mining Twitter®: Sentiment Analysis, JSON and Web Services
- DS 14. IBM Watson® and Cognitive Computing
- DS 15. Machine Learning: Classification, Regression and Clustering
- DS 16. Deep Learning Convolutional and Recurrent Neural Networks; Reinforcement Learning in the Exercises
- DS 17. Big Data: Hadoop®, Spark(TM), NoSQL and IoT
| Erscheinungsjahr: | 2019 |
|---|---|
| Fachbereich: | Programmiersprachen |
| Genre: | Informatik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Seiten: | 880 |
| ISBN-13: | 9780135404676 |
| ISBN-10: | 0135404673 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: |
Deitel, Paul
Deitel, Harvey |
| Hersteller: | Pearson Education |
| Maße: | 232 x 182 x 29 mm |
| Von/Mit: | Paul Deitel (u. a.) |
| Erscheinungsdatum: | 15.02.2019 |
| Gewicht: | 1,212 kg |
Paul J. Deitel, CEO and Chief Technical Officer of Deitel & Associates, Inc., is an MIT graduate with 38 years of computing and corporate training experience and is an Oracle® Java® Champion and a Microsoft® C# MVP (2012-2014). He is a best-selling programming-language textbook/professional book/video/e-learning author. Paul is one of the world's most experienced programming-languages trainers. Through Deitel & Associates, Inc., he has delivered hundreds of programming courses worldwide to clients, including Cisco, IBM, Siemens, Sun Microsystems (now Oracle), Dell, Fidelity, NASA at the Kennedy Space Center, the National Severe Storm Laboratory, White Sands Missile Range, Rogue Wave Software, Boeing, SunGard Higher Education, Nortel Networks, Puma, iRobot, Invensys and many more. He and his co-author, Dr. Harvey M. Deitel, are the world's best-selling programming-language textbook/professional book/video authors.
Dr. Harvey M. Deitel, Chairman and Chief Strategy Officer of Deitel & Associates, Inc., has over 55 years of experience in computing. Dr. Deitel earned B.S. and M.S. degrees in Electrical Engineering from MIT and a Ph.D. in Mathematics from Boston University-he studied computing in each of these programs just before they spun off Computer Science programs. He has extensive college teaching experience, including earning tenure and serving as the Chairman of the Computer Science Department at Boston College before founding Deitel & Associates, Inc., in 1991 with his son, Paul. The Deitels' publications have earned international recognition, with more than 100 translations published in Japanese, German, Russian, Spanish, French, Polish, Italian, Simplified Chinese, Traditional Chinese, Korean, Portuguese, Greek, Urdu and Turkish. Dr. Deitel has delivered hundreds of programming courses to academic, corporate, government and military clients.
- PART 1
- CS: Python Fundamentals Quickstart
- CS 1. Introduction to Computers and Python
- DS Intro: AI-at the Intersection of CS and DS
- CS 2. Introduction to Python Programming
- DS Intro: Basic Descriptive Stats
- CS 3. Control Statements and Program Development
- DS Intro: Measures of Central Tendency-Mean, Median, Mode
- CS 4. Functions
- DS Intro: Basic Statistics- Measures of Dispersion
- CS 5. Lists and Tuples
- DS Intro: Simulation and Static Visualization
- PART 2
- CS: Python Data Structures, Strings and Files
- CS 6. Dictionaries and Sets
- DS Intro: Simulation and Dynamic Visualization
- CS 7. Array-Oriented Programming with NumPy, High-Performance NumPy Arrays
- DS Intro: Pandas Series and DataFrames
- CS 8. Strings: A Deeper Look Includes Regular Expressions
- DS Intro: Pandas, Regular Expressions and Data Wrangling
- CS 9. Files and Exceptions
- DS Intro: Loading Datasets from CSV Files into Pandas DataFrames
- PART 3
- CS: Python High-End Topics
- CS 10. Object-Oriented Programming
- DS Intro: Time Series and Simple Linear Regression
- CS 11. Computer Science Thinking: Recursion, Searching, Sorting and Big O
- CS and DS Other Topics Blog
- PART 4
- AI, Big Data and Cloud Case Studies
- DS 12. Natural Language Processing (NLP), Web Scraping in the Exercises
- DS 13. Data Mining Twitter®: Sentiment Analysis, JSON and Web Services
- DS 14. IBM Watson® and Cognitive Computing
- DS 15. Machine Learning: Classification, Regression and Clustering
- DS 16. Deep Learning Convolutional and Recurrent Neural Networks; Reinforcement Learning in the Exercises
- DS 17. Big Data: Hadoop®, Spark(TM), NoSQL and IoT
| Erscheinungsjahr: | 2019 |
|---|---|
| Fachbereich: | Programmiersprachen |
| Genre: | Informatik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Seiten: | 880 |
| ISBN-13: | 9780135404676 |
| ISBN-10: | 0135404673 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: |
Deitel, Paul
Deitel, Harvey |
| Hersteller: | Pearson Education |
| Maße: | 232 x 182 x 29 mm |
| Von/Mit: | Paul Deitel (u. a.) |
| Erscheinungsdatum: | 15.02.2019 |
| Gewicht: | 1,212 kg |
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