Join us for a special IBM Watson Studio three-part masterclass.  You can attend all three or pick and choose the ones that best fit your needs.

✅ Part 1: Building and Deploying models with Visual Recognition and Natural Language Classifier → May 11th

Come learn how to quickly store, train, test and deploy custom visual recognition and natural language model with Watson Studio! You will learn how to quickly and accurately tag, classify, and train and manage your visual and natural language data, using machine learning in a secure cloud environment!

Learn how to build, classify and train custom visual content and natural language using machine learning

** Get a head start by signing up for a free IBM Cloud account via → https://ibm.biz/BdqqiN **

12:30 pm: Event kick-off & Getting Setup on IBM Cloud

Pooja Mistry (@poojamakes) is a Developer Advocate for the IBM Cloud Platform. She works on expanding the reach of IBM's technology to New York City's developer community. Her area of interest includes prototyping with Node-RED, analyzing data, creating custom models with AI/ML services, NLU/NLP, building chatbots, and using open source libraries and SDKs to develop fun and exciting projects! Pooja is passionate about the intersection of technology and the community. She loves to learn, teach, and share her knowledge with the developer ecosystem. She strongly believes in helping new technologists get up and running with technology and feel confident in their abilities to make!

Jenna Ritten (@jritten) is a cloud software developer turned developer advocate for IBM Cloud. She works on expanding the reach of open source technologies to Detroit and Austin's developer communities. Her areas of interest include hackathons, design-thinking workshops, NLU/NLP, gamified learning, and Blockchain. Jenna left Detroit to attend Dev Bootcamp San Francisco to learn full-stack web development before joining IBM Austin as part of the Tech Re-Entry program. She is an advocate for non-traditional people in tech, much like herself, and provides support by building and fostering communities for underrepresented people in tech.

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✅ Part 2: Building and Deploying models with AutoAI → May 18th

Come learn how to build and deploy your very own AI predictive models. IBM Watson Studio AutoAI automatically analyzes your data and generates customized predictive model pipelines. Using AutoAI, you can build and deploy a machine learning model with sophisticated training features and no coding!

Learn about Data Pre-Processing and Automated Model Selection

Learn about Automated Feature Engineering and Hyperparameter Optimization

✅ Part 3: Building and Deploying models with Jupyter Notebooks → May 26th

Come learn how to use Juypter Notebooks in a secure cloud environment to analyze data. You will learn how to prepare and normalize the data for machine model building, split data into training sets for model validation, train the model by using machine learning algorithms and finally deploy the model so that it can be accessed outside of the notebook.

Basics of Jupyter Notebooks on Watson Studio

Learn how to normalize, split, train with Python and deploy data in a Jupyter Notebook

AI/ML Masterclass Part 1: Building and Deploying models with Visual Recognition and Natural Language Classifier