Data Science and AI for Python Programmers
Instructor-Led, On-Site Training with Paul DeitelIntended for Python programmers and based on our innovative new textbook Intro to Python for Computer Science and Data Science, this course provides a code-intensive introduction to today’s most compelling, leading-edge data science, AI and big data computing technologies, with cool examples on natural language processing, 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 Hadoop®, Spark™ streaming, NoSQL databases and the Internet of Things.
Attendees leverage key, open-source, Python data-science libraries, Python AI libraries and infrastructure platforms to quickly create powerful applications with minimal code.
Key Topics
- Natural Language Processing—TextBlob, Textatistic, spaCy and word_cloud
- Data Mining Twitter—Sentiment analysis, Tweepy, JSON, streaming tweets, word_cloud
- IBM Watson and Cognitive Computing—Building an inter-language speech-to-speech translator
- Supervised Machine Learning—Classification and linear regression with scikit-learn, Seaborn and Matplotlib
- Unsupervised Machine Learning—Clustering with scikit-learn
- Deep Learning for Computer Vision—Convolutional neural network in Keras running over TensorFlow
- Deep Learning for Sentiment Analysis—Recurrent neural network in Keras running over TensorFlow
- MongoDB NoSQL Document Database—Storing streaming tweets as JSON documents and visualizing with an interactive folium map
- Hadoop—MapReduce with Hadoop Streaming running on a Microsoft Azure cluster
- Spark—Spark and Spark Streaming running on a juypyter/pyspark-notebook Docker container
- Internet of Things (IoT) Streaming Data—Simulated streaming sensors with dweet.io, dweepy and PubNub; simulated streaming stock prices with PubNub; and visualizing streaming data with freeboard.io and Seaborn
Intended Audience
- Python programmers who see exciting AI, big data and data science technologies popping up everywhere and who want a code-intensive introduction to them.
- Python programmers looking to enhance their career opportunities with these current technologies.
- Managers contemplating Python projects using AI, big data and data science technologies who want a code-intensive introduction to them.
- R programmers whose organizations are considering Python and who want a code-intensive introduction to Python’s AI, big data and data science capabilities. For the best experience, R programmers should first take our Python for Programmers course.
- Programmers who have taken our Python for Programmers course.
Instructor
Paul J. Deitel, CEO and Chief Technical Officer of Deitel & Associates, Inc., is an MIT graduate with 38 years of experience in computing. Paul is one of the world’s most experienced programming-languages trainers, having taught professional courses to software developers since 1992.
Share This Page