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Cognitive Class is an online learning platform offering a range of courses and resources to help people become data and AI-ready.
Build and run container images, write YAML deployment files, expose services, and manage apps with Kubernetes using ReplicaSets, auto-scaling, rolling updates, OpenShift and Istio.
Build an IoT blockchain network for a supply chain, connecting devices to a shared ledger that tracks goods as they move between parties.
Build and deploy a code-free chatbot with Watson Assistant: create intents, entities and dialogs, use context variables, slots and digressions, then publish to WordPress.
Get hands-on with data science tools: Jupyter Notebooks, RStudio IDE, GitHub, and Watson Studio, then build and share a notebook with Markdown in the cloud.
Learn Spark fundamentals: work with RDDs and DataFrames, program applications with SparkContext in Scala and Python, use Spark libraries, and configure, monitor and tune clusters.
Learn to build cloud native applications: break monoliths into microservices, deploy containers to Kubernetes and OpenShift, and build CI/CD pipelines for hybrid and multicloud environments.
Learn Apache Hadoop's architecture and administration: how HDFS stores data, the MapReduce philosophy, adding and removing cluster nodes, and ecosystem tools like Pig, Hive, Sqoop, and Oozie.
Learn privacy through five 2012–2015 data breaches, including Target and Home Depot, plus Canadian privacy laws, PIPEDA, and the 7 Privacy by Design principles.
Learn a repeatable, business-oriented DataOps framework for building and deploying analytics and data pipelines, applying data governance and model management practices to deliver trusted enterprise data.
Big Data is NoHadoop and NoSQL: examine what Big Data is and how a platform handles variety, velocity, and volume through integrated components and data governance.
Build IoT apps for robots using Watson services, Swift, and Node-RED flows.
Learn R fundamentals using movies data: vectors, lists, matrices, data frames, conditionals, functions, classes, debugging, reading CSV, Excel and text files, regular expressions and dates.
Build and program a TJBot robot.
Use Scala with Apache Spark to tackle big data analytics: build Spark machine learning pipelines, fit models, and search for optimal hyperparameters on a cluster.
Build deep learning models in TensorFlow: linear, nonlinear and logistic regression, convolutional and recurrent networks with LSTM, restricted Boltzmann machines, and autoencoders.
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