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Big Data LDN
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Watson
Cloud Pak for Data
AWS
Azure
Multicloud
Register for this course and see more details by visiting:
OpenCourser.com/course/peyzz1/bring
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Designed for experienced data and AI professionals looking to unify and scale their AI efforts in a multicloud environment
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Bring the Power of Watson to AWS and Azure: Watson Anywhere Powered by Cloud Pak for Data.
These are activities you can do either before, during, or after a course.
Career center
Learners who complete Bring the Power of Watson to AWS and Azure: Watson Anywhere Powered by Cloud Pak for Data will develop knowledge and skills
that may be useful to these careers:
AI Engineer
AI Engineer
AI Engineers design, develop, and implement AI systems. They may use Watson Anywhere to implement, unify, and scale AI efforts in a multicloud environment. This course can help build a foundation for that work, particularly the Watson Anywhere Powered by Cloud Pak for Data material.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain data pipelines and infrastructure. They may use Watson Anywhere to implement, unify, and scale AI efforts in a multicloud environment. This course can help build a foundation for that work, particularly the Watson Anywhere Powered by Cloud Pak for Data material.
Cloud Architect
Cloud Architect
Cloud Architects design and manage cloud computing environments for organizations. They may use Watson Anywhere to implement, unify, and scale AI efforts in a multicloud environment. This course can help build a foundation for that work, particularly the Watson Anywhere Powered by Cloud Pak for Data material.
Big Data Engineer
Big Data Engineer
Big Data Engineers design, build, and maintain big data systems. They may use Watson Anywhere to implement, unify, and scale AI efforts in a multicloud environment. This course can help build a foundation for that work, particularly the Watson Anywhere Powered by Cloud Pak for Data material.
Data Management Architect
Data Management Architect
Data Management Architects design and implement data management solutions for organizations. Use of Watson Anywhere is likely when building a cloud-native Data and AI platform which leverages innovative Watson AI services. This course can help build a foundation for that work, particularly the Watson Anywhere Powered by Cloud Pak for Data material.
Business Analyst
Business Analyst
Business Analysts use their knowledge of business and technology to help organizations solve problems and improve performance. They may use Watson Anywhere to implement, unify, and scale AI efforts in a multicloud environment. This course can help build a foundation for that work, particularly the Watson Anywhere Powered by Cloud Pak for Data material.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. They may use Watson Anywhere to implement, unify, and scale AI efforts in a multicloud environment. This course can help build a foundation for that work, particularly the Watson Anywhere Powered by Cloud Pak for Data material.
Systems Engineer
Systems Engineer
Systems Engineers design, build, and maintain computer systems. They may use Watson Anywhere to implement, unify, and scale AI efforts in a multicloud environment. This course can help build a foundation for that work, particularly the Watson Anywhere Powered by Cloud Pak for Data material.
DevOps Engineer
DevOps Engineer
DevOps Engineers work to bridge the gap between development and operations teams. They may use Watson Anywhere to implement, unify, and scale AI efforts in a multicloud environment. This course can help build a foundation for that work, particularly the Watson Anywhere Powered by Cloud Pak for Data material.
Data Architect
Data Architect
Data Architects are responsible for designing, creating, and maintaining the data infrastructure of an organization. This role might use Watson Anywhere to design a cloud-native Data and AI platform which leverages innovative Watson AI services. This course can help build a foundation for that work, particularly the Watson Anywhere Powered by Cloud Pak for Data material.
Data Scientist
Data Scientist
Data Scientists leverage mathematics and statistics to help businesses understand and use data to make better decisions. They may use Watson Anywhere to build, deploy, and manage AI models in the cloud. This course can help build a foundation for that work, particularly the Watson Anywhere Powered by Cloud Pak for Data material.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers use their knowledge of computer science and software engineering to build, deploy, and manage machine learning models in production. They may use Watson Anywhere to work with a cloud-native Data and AI platform which leverages innovative Watson AI services. This course can help build a foundation for that work, particularly the Watson Anywhere Powered by Cloud Pak for Data material.
Data Analyst
Data Analyst
Data Analysts combine their knowledge of mathematics, data, and AI to solve business challenges. Through statistical and mathematical modeling, they may use Watson Anywhere to create actionable insights from data in order to inform better decision making. This course can help build a foundation for that work, particularly the Watson Anywhere Powered by Cloud Pak for Data material.
Project Manager
Project Manager
Project Managers plan, execute, and close projects. They may use Watson Anywhere to implement, unify, and scale AI efforts in a multicloud environment. This course can help build a foundation for that work, particularly the Watson Anywhere Powered by Cloud Pak for Data material.
Product Manager
Product Manager
Product Managers are responsible for the development and management of products. They may use Watson Anywhere to implement, unify, and scale AI efforts in a multicloud environment. This course can help build a foundation for that work, particularly the Watson Anywhere Powered by Cloud Pak for Data material.
For more career information including salaries, visit:
OpenCourser.com/course/peyzz1/bring
Reading list
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Discusses the challenges and opportunities of AI, and how we need to prepare for the future. It also provides insights into the Chinese perspective on AI.
Provides a comprehensive overview of deep learning for natural language processing. It covers topics such as word embeddings, recurrent neural networks, and transformers.
Provides a hands-on introduction to machine learning, with a focus on practical applications. It covers topics such as supervised learning, unsupervised learning, and data visualization.
Provides a comprehensive overview of data science, with a focus on business applications. It covers topics such as data collection, data cleaning, data analysis, and data visualization.
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Provides a comprehensive overview of big data analytics, with a focus on its business applications. It covers topics such as data collection, data cleaning, data analysis, and data visualization.
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Discusses the use of predictive analytics to make better decisions and predictions. It covers topics such as data mining, machine learning, and statistical modeling.
Discusses the use of data to drive marketing decisions. It covers topics such as customer segmentation, customer lifetime value, and campaign measurement.
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Discusses the use of the lean startup methodology to build successful businesses. It covers topics such as customer development, product development, and business model innovation.
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Provides insights into how to execute business strategies and achieve results. It covers topics such as leadership, teamwork, and accountability.
Discusses the challenges that large companies face when innovating. It covers topics such as the innovator's dilemma, disruptive innovation, and corporate culture.
Covers the latest AWS certification exam blueprint and provides comprehensive coverage of all exam topics. It is an excellent resource for anyone preparing for the AWS Certified Solutions Architect - Professional exam.
Provides a comprehensive overview of AWS for architects and covers topics such as cloud design principles, architectural patterns, and best practices. It valuable resource for anyone looking to design and deploy cloud applications on AWS.
Provides a comprehensive overview of AWS security best practices and covers topics such as identity and access management, data protection, and network security. It valuable resource for anyone looking to secure their AWS environment.
Provides a comprehensive overview of AWS and covers topics such as core services, cloud design principles, and best practices. It valuable resource for anyone looking to get started with AWS.
Provides a comprehensive overview of serverless computing on AWS and covers topics such as building and deploying serverless applications, using AWS Lambda, and managing serverless infrastructure. It valuable resource for anyone looking to build serverless applications on AWS.
Provides a comprehensive overview of AWS systems operations and covers topics such as managing EC2 instances, working with Amazon RDS, and using AWS CloudFormation. It valuable resource for anyone looking to operate and manage AWS infrastructure.
Covers the latest AWS certification exam blueprint and provides comprehensive coverage of all exam topics. It is an excellent resource for anyone preparing for the AWS Certified Developer Associate exam.
Covers the latest AWS certification exam blueprint and provides comprehensive coverage of all exam topics. It is an excellent resource for anyone preparing for the AWS Certified Advanced Networking - Specialty exam.
Covers the latest AWS certification exam blueprint and provides comprehensive coverage of all exam topics. It is an excellent resource for anyone preparing for the AWS Certified DevOps Engineer - Professional exam.
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Explores the potential impact of AI on our lives, our work, and our world. It discusses the ethical and social implications of AI, and how we need to prepare for the future.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/peyzz1/bring
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Big Data LDN
This course belongs to a
collection
called
Big Data LDN 2019 . It's comprised of 101 courses:
- The Database Is Only Half Done
- Your AI Is Wrong! Lessons from Decision-making with Imperfect AI
- Multiparadigm Data Science: The Next Frontier in Decision Making
- Achieving 100% Adoption of Analytics in the Enterprise
- Data Skills: How Mondi Does Digital
- Building a Modern Data Architecture for the Data Driven Enterprise
- Harnessing the Power of Data to Improve Public Health
- Real-time Data Analytics at Scale Using Cloud Services
- Quick and Easy Access to Data through a Logical Data Warehouse Environment
- The Promise of Data Mastering at Scale
- Research vs. Reality in AI: Would You Trust Your Model with Your Life?
- Modernise Your IT Infrastructure for AI
- Scaling Machine Learning at Holiday Extras
- Why Do Some Machine Learning Models Fail?
- AI: Lessons Learned from the Front Line
- Machine Learning in Real-time: Predicting Taxi Fare in NYC
- How AI and Automated Machine Learning Will Disrupt the Organisational Alignment of Businesses
- Multi-model Powered Machine Learning
- ML in Production: Serverless and Painless
- Leveraging Data Virtualization to Maximize Advanced Analytics and Machine Learning Potential in Your Data Architecture
- Bring the Power of Watson to AWS and Azure: Watson Anywhere Powered by Cloud Pak for Data (viewing)
- Modern Data Warehousing at Scale Using Azure Data Factory
- Balancing Performance, Scalability, and High Availability in Your Database Environment
- Enabling Microservices for Big Data On-demand in the Cloud
- From ETL to ELT: Building a Scalable Data Stack with SQL
- Data, Governance, and Freedom
- How to Get the Technology Stack Right for Your Business
- Data Modelling with Apache Cassandra
- How to Orchestrate Your ML Pipelines in Hybrid Cloud
- Full Stack Metadata Driven Thinking to Drive Business Agility
- Enhance Developer Experience Using OpenShift on Azure
- Fast Data for Faster Business
- Driving Faster, Smarter Actions on IoT Data with New Real-time Analytics Capabilities
- Introduction to Adept and How Big Data and Analytics Is Transforming the Connected Car Ecosystem
- Bridge to Cloud
- How to Train Your AI Models at Scale
- 99% of Your IoT Data Is Worthless, but Which 99%?
- Data Engineering in MagicLab: The Birth and Life of an Event
- RNA - Event Stream Processing Made Simple
- When Data Leads, Transformation Follows - A Look at Qlik's Data Integration Portfolio
- Saving Energy in Homes with a Unified Approach to Data and AI
- Building Stream Processing Applications with Apache Kafka Using KSQL
- Real-world, Real-time Digital Transformation
- Machine Data in Industry 4.0: How to Handle It Better
- Why CockroachDB in the Kindred Platform?
- The Hardest Part of AI & Analytics Is Not AI, It Is Data Management
- Effective Cloud Migration Strategies for Your Modern Data Applications
- Snowflake? Why Should I Care?
- The Future of Business Intelligence Isn't a Tool
- AI-driven Retail for the 21st Century
- The Next Generation of Data Architecture
- Modern Enterprise Data Engineering
- Taking Control of User Analytics with Snowplow
- Flex Your Data(Ops) Muscles
- You Love Big Data, so Does R
- Building Predictive Maintenance Solutions
- Quickly, Codelessly Connect Any Application to Any REST API
- Rethinking Data Warehouse Modernization in the Age of Hybrid Cloud/On-premise Data Warehouses
- From Waterfall to Agile – A Data Warehouse Modernisation Story
- Freeing up Engineering and Infrastructure Resources to Scale with DataOps
- Unit Testing with pytest
- Credit Card Fraud – Why the Database Matters
- Data Science at SEGA
- British Telecom: Data-driven Digital Transformation
- Using Cloud Solution Platforms to Drive Business Value and Cost Optimization
- Data Analytics & IoT Innovations at Bosch
- Converting the CDO to a Profit Centre
- Why Self-service Data Analytics Usually Fails & Ideas for Succeeding
- Governed Data Discovery
- Journey to Create a Great Analytic Culture
- Something Amazing for Everyone: Embracing Inclusive Design to Deliver Accessible Experiences
- Democratising Data – How We Built a Self-serve Data Platform
- Discover the “Why” You Didn't Know Existed
- Selecting Your Fantasy Premier League Team with Advanced Analytics
- Decouple Storage from Compute
- Data Skills: Building a Data Team Fit for a Data-driven Enterprise
- Consent, Compliance, and the Impact on Customer Experience
- AI & Communication: Meaningful Data from New Sources
- Real-time Personalised Customer Interaction at Scale
- Data: The Musical, with LW Theatres
- Self-service and Tableau Community at Lloyds Banking Group
- The Digital Hero’s Journey: Using Big Data to Uncover Business Value and Meaning at Work
- Using Location Intelligence to Place Solar Panels in Rwanda
- Embedding Intelligence into the Heart of Customer Operations
- The Art of Customer Conversations
- How to Build a Fully Autonomous Card Fraud Detection System
- At Last! The Real-time Customer Experience
- Data Privacy Mythbusting
- Demystifying Data – What They Don’t Tell You at Data School
- Optimizing Your Data Value Chain with Agile Data Management
- Data at SEGA Europe
- Keep Your Data Lake from Getting Hadooped
- Top 10 Privacy Tips & Tricks in Big Data
- Data Governance as a Customer Service
- 7 AI Quick Win Projects
- Delivering Value with Intelligent Data Governance
- The Culture Competition – Personalisation vs. Privacy
- DataOps for AI and Digital Transformation
- Big Data LDN: A GDPR Retrospective
- GDPR: A Sword Not a Shield
- Drive Business Growth While Satisfying GDPR and CCPA
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