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    • Average client rating (based on 26 attendee reviews)

Intro to AI with Machine Learning, Deep Learning and More

Level: Skill | Type: Remote Instructor Led Series | Discipline: Data Science

A five-day, lecture and hands-on lab course for people who have completed the Intro to Python course, people who have completed the Intro to Python for Non-Programmers: Parts 1 & 2 course sequence, or people with equivalent Python programming experience.

Course Overview

Intended for Python programmers and based on the innovative textbook Intro to Python for Computer Science and Data Science: Learning to Program with AI, Big Data and the Cloud (https://deitel.com/IntroToPythonContentsDiagram) by Paul Deitel and Harvey Deitel, this course provides a code-intensive introduction to some of today’s most compelling, leading-edge data science, AI and big data computing technologies, with cool examples on natural language processing, data visualization, data mining Twitter® for sentiment analysis, cognitive computing with IBM® Watson™, supervised machine learning with classification and regression, unsupervised machine learning with clustering, computer vision through deep learning with a convolutional neural network, sentiment analysis through deep learning with a recurrent neural network, and big data with Spark™ streaming, NoSQL databases and the Internet of Things (IoT).

Attendees leverage key, open-source, Python data-science libraries, Python AI libraries and infrastructure platforms to maximize productivity, quickly creating powerful applications with minimal code. The course offers extensive hands-on lab coding practice. Deitel LabAssist notes provide hints for each hands-on lab, enabling you to work through many labs efficiently.

About Your Instructor

Paul Deitel, CEO and Chief Technical Officer of Deitel & Associates, Inc., is an MIT graduate with 40 years in computing. He is one of the world’s most experienced programming-languages trainers, having taught hundreds of instructor-present and virtual courses worldwide (based on his Pearson Education programming-language college textbooks and professional books) to software developers of all skill levels since 1992. He is a top author on O’Reilly Online Learning where his Python Fundamentals LiveLessons, Java Fundamentals LiveLessons and C# Fundamentals LiveLessons 50+ hour asynchronous video courses have ranked #1 eight of the last 12 years among 6,000 video products from 200+ publishers. Thousands of users have viewed his asynchronous streaming Python Fundamentals LiveLessons videos for over 10.5 million contact minutes. 10,000+ students have attended his live (synchronous), one-day, code-intensive Python Full Throttle and Python Data Science Full Throttle courses for over 2.7 million live contact minutes.

Together, he and his co-author, Dr. Harvey M. Deitel, are among the world’s best-selling programming-language textbook, professional book, video and interactive multimedia e-learning authors, having written 100+ Pearson Education/Prentice Hall college textbooks and professional books on Python, Java, C++, C, C#, Internet/Web, Android, iOS, Swift, Visual Basic and more. Their books have 100+ translations into Italian, Japanese, German, Russian, Spanish, French, Polish, Simplified Chinese, Traditional Chinese, Korean, Portuguese, Greek, Urdu and Turkish.

Deitel clients include some of the world’s largest companies, government agencies, branches of the military, and academic institutions—SLB, UCLA Anderson School of Management, Cisco, IBM, Siemens, Sun Microsystems (now Oracle), Dell, Fidelity, NASA at the Kennedy Space Center, White Sands Missile Range, the National Oceanic and Atmospheric Administration (NOAA), the National Severe Storm Laboratory, Rogue Wave Software, Boeing, Puma, iRobot and many more.


Customize your learning journey

Customize your own learning journey and track your progress when you start using a defined learning path.

In just few simple steps, you can customize your own learning journey in the discipline of your interest, based on your immediate, intermediate and transitional goals. Once done, you can save it in NExTpert-the digital learning ecosystem-and track your progress.

Explore arrow_forward

  • Natural Language Processing
  • Data Mining Twitter with the tweepy library
  • IBM Watson and Cognitive Computing
  • Supervised Machine Learning with the scikit-learn library: Classification and Regression
  • Unsupervised Machine Learning with the scikit-learn library: Dimensionality Reduction and Clustering
  • Deep Learning for Computer Vision with Keras, Tensorflow and a Convolutional Neural Network (CNN)
  • Deep Learning for Sentiment Analysis with Keras, Tensorflow and a Recurrent Neural Network (RNN)
  • Big Data: Relational Databases with the sqlite library
  • Big Data: NoSQL Case Study—A MongoDB JSON Document Database using the pymongo library
  • Big Data: Apache Spark and the pyspark library
  • Big Data: Internet of Things and Dashboards with freeboard.io, dweet.io, dweepy and pubnub

  • Python programmers who see exciting AI, machine learning, deep learning, big data and data science technologies popping up everywhere and who want a broad-based, code-intensive introduction to them.
  • Managers contemplating Python projects for their teams using AI, machine learning, deep learning and big data technologies and who want a code-intensive introduction to them.
  • Programmers who have taken the Intro to Python course.
  • R programmers whose organizations are considering adding or switching to Python and who want a code-intensive introduction to Python’s AI, machine learning, deep learning and big-data capabilities. For the best experience, R programmers should first take our Intro to Python course.
  • People who have taken the Intro to Python for Non-Programmers

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