On November 24th, you will have a chance to obtain IBM free Badge and Special offer from IBM & Coursera
IBM is running a free, online Data & AI Conference for India and the Asia Pacific region, covering four dedicated tracks:
- AI in production
- Five hands-on labs
- Data and AI essentials course
- Data competitions and open source
Register for free and get ready to build smart and secure data and AI solutions on hybrid cloud with trust, resilience, and robustness.
During the conference, you’ll grow your expertise on IBM and open source technologies to build AI-centric platforms.
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Benefits- IBM free Badge and Special offer from IBM & Coursera
Table of Contents
You will be able to earn a Data & AI Essentials badge for attending the conference
IBM partnered with Coursera to give attendees an amazing offer — four free certifications:
- IBM AI Enterprise Workflow Specialization (4 months)
- IBM Machine Learning Professional Certificate (6 months)
- IBM Data Science Professional Certificate (10 months)
- Advanced-Data Science with IBM Specialization (4 months)
Beyond those $800-worth of courses, attendees get $300 in credits to spend on any services in the IBM Cloud Catalog, which is just mind-blowing.
What You’ll Learn
AI in production
Clients share their challenges, and how they overcame them, through architectural and tooling solutions. Session topics include deploying models on the edge, cloud-based AI development environments, building personalized messaging at scale with AI, and the latest from IBM Research.
Day 1: November 24, 2020
- Keynote 1 – Scaling enterprise AI: An IBM Research perspective
- Keynote 2: Concerns and mitigating risk of deploying AI in production
- Data+ML to predict media impact on sales
- Open data science meets the enterprise: Challenges and opportunities
- Designing an AI Captain for the Mayflower Autonomous Ship
- Francesca Rossi and AI ethics
- Fantasy football insights & US Open
- Building the Weather.com Covid-19 dashboard and trusted data lake
- Software is eating the world – can AI eat software?
- Drive actionable insights from your high-value Z data with Watson Machine Learning for z/OS
- Red Hat OpenShift: It’s better to share, integrate and automate
- Driving agility in Cora by leveraging containers and CI/CD
Hands-on labs
Focused on the next level AI, ML, and data science these detailed walkthrough cover common design patterns used by developers today for the challenges of tomorrow. Session topics include AI fairness and bias detection and mitigation, deep reinforcement learning in finance, and building AutoAI pipeline for cyberthreat detection.
Day 1: November 24, 2020
- Keynote 1 – Scaling enterprise AI: An IBM Research perspective
- Keynote 2: Concerns and mitigating risk of deploying AI in production
- Deploy deep learning models as microservices using open source tools
- Building AutoAI pipelines for cyber threat detection
- Beyond accuracy: Fairness in machine learning
- Building smarter conversational AI
- Deep reinforcement learning in finance – Trading using Ray and RLlib
Data & AI Essentials course
Using AI in the real world requires more than just training machine learning models. It involves the entire AI lifecycle including data collection, preparation, and analysis as well as operationalizing the models. And as we scale AI to larger enterprise applications, we face even more challenges such as data decentralization, compliance, regulations, model drift, etc. In this course, we set out to address these challenges and show you how you can go from data to fully deployed models in production. Join us in this course to learn how you can address these problems and earn an industry recognizable Data & AI Essentials digital badge.
Day 1: November 24, 2020
- Overview – Data & AI Essentials Course
- Chapter 1: Introduction
- Chapter 2: Getting Set Up – [Talk] Overview of IBM Cloud Pak for Data as a Service
- Chapter 2: Getting Set Up – [Lab] Project Set Up
- Chapter 3: Data Preparation – [Talk] Processing Overview
- Chapter 3: Data Preparation – [Lab] Data Preparation using Data Refinery
- Chapter 4: Data Organization – [Talk] Overview of Watson Knowledge Catalog
- Chapter 4: Data Organization – [Demo] Watson Knowledge Catalog in action
- Chapter 5: Analyze – [Talk] Overview of Machine Learning
- Chapter 5: Analyze – [Lab] Building AI Model in Jupyter Notebooks
- Chapter 5: Analyze – [Lab] Automated Model Builds with AutoAI
- Chapter 6: Deployment – [Talk] Overview of Model Deployment
- Chapter 6: Deployment – [Lab] Online Model Deployment
- Chapter 6: Deployment – [Lab] Batch Scoring Deployment
- Chapter 6: Deployment – [Lab] Using Your Model In a Python Application
- Chapter 7: Infuse – [Talk] Monitoring your models in production overview
- Chapter 7: Infuse – [Demo] Monitoring your models with OpenScale
- Chapter 8: Conclusion and the badge
Data competitions & Open Source
Experienced data scientists share best practices on model accuracy and winning data competitions, plus get the latest on the future of open source and state-of-the-art AI and ML, and be the first to learn about a new data competition from IBM.
Introducing Call for Code Spot Challenge on Wildfires
Join a team of coders and data scientists to develop models to forecast potential wildfires in Australia in preparation for the upcoming 2021 wildfires season. We’re excited to share data from the IBM Weather Operations Center Geospatial Analytics Center going back to 2005 for this project. Make a difference and maybe win a prize!
Day 1: November 24, 2020
- Keynote 1 – Scaling enterprise AI: An IBM Research perspective
- Keynote 2: Concerns and mitigating risk of deploying AI in production
- [Call for Code] Introduction to the competition: Predicting bushfires
- [Call for Code] Getting Started with the Wildfires Dataset by Margriet Groenendijk
- [Call for Code] Getting Started with AutoAI and the Wildfires Dataset
- Building and using stacked machine learning models – A proven path to more accurate models
- Creating inclusive IT language, a fireside chat
- Ways you can get involved in the Women in Data Science (WiDS) program
- What’s next in Open Source Data Science & AI?
Live Watch Party
IBM Developer Advocates Spencer Krum, JJ Ashgar, and Matt Hamilton host a watch party during the conference. Sessions speakers and other developer experts stop by to hang out, do some live coding, and answer your questions.
Call for Code Spot Challenge on Wildfires
You’ll also have the opportunity to join a team of coders and data scientists in “Call for Code Spot Challenge on Wildfires,” where you’ll develop models to forecast wildfires in Australia n preparation for the upcoming 2021 wildfires season. This challenge is a great opportunity to make a difference along with the chance of winning a prize!
Featured speaker spotlight in IBM free Badge and Special offer from IBM & Coursera
This conference is packed with industry leaders
If you haven’t signed up for the conference already, now is the best time to signup
I hope you take full advantage of this grand event to upskill and grow in your IT Career.