The Artificial Intelligence career path will help the audience understand AI domains such as Machine Learning algorithms, neural networks, supervised and unsupervised learning, and AutoAI, to design, analyze, and develop cognitive solutions applied in the real world. Training topics will include AI, IBM Watson, hands-on and case studies on machine learning, NLP, and chatbots.

The Predictive Analytics Modeler career path will help the audience understand essential analytics models that can help collect and analyze data efficiently. Training topics will include data mining, data collection and integration, nodes, and statistical analysis. These tools help businesses perform market analysis and data mining in order to predict problems and improve outcomes.

The Big Data Engineer career path will help the audience understand the Big Data platform and its methodologies to collect and analyze large amounts of data, using tools such as Apache Hadoop, Ambari, Spark, HDFS, YARN, MapReduce, Hive, and HBase. Training topics will include provisioning, managing, and monitoring your data platform; Storing and querying data efficiently; Security and data governance; integrate data from multiple data resources on the cloud; and use machine learning algorithms to perform analysis.

The Business Intelligence Analyst career path will help the audience learn how to collect and analyze data, to make better business decision making. Teaching topics include report building techniques using relational data models; enhance, customize, and manage professional reports; active reports content and functionality; and data graphics and RAVE visualization.

The Cloud Application Developer career path will help the audience learn how to develop, build, deploy, and test Software as a Service (SaaS) solutions using a cloud platform. Training topics include Kubernetes, Artificial Intelligence, etc

The Cloud Native Application Developer career path will help the audience develop, deploy, and manage applications to build solutions running on Public, Private and Hybrid clouds. Training topics include hybrid cloud concepts and benefits, application modernization, microservices, microservices integration, container technology and applications, and Kubernetes.

The IoT Cloud Developer career path will help the audience understand IoT concepts such as connectivity protocols, data generated by sensors and other devices, cloud computing, flow-based programming, edge computing, and analytics, to apply in practical use cases by using IBM Watson IoT Platform, AI services, and tools and services on IBM Cloud.

The Blockchain Developer career path will help the audience understand the fundamentals of blockchain with a focus on developing solutions in enterprise environments. Training topics include Hyperledger Fabric, business network, smart contracts, chaincode development lifecycle, blockchain security, and data privacy.

The Security Intelligence Engineer career path will help the audience learn how to consolidate event logs from device endpoints within a network to identify and prevent threats. Training topics include security intelligence, event management, data security, event offenses, asset profile offenses, and event rules.