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Big Data LDN
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AI Models
Training AI Models
Scaling AI Models
Redis
Personalization
Recommendation
Fraud Detection
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Teaches learners to utilise Redis, a performant database with features that include seamless scalability and high availability
Covers the ability to automate data management processes in Redis, allowing learners to optimise workflows
Utilizes real-world examples to demonstrate the application of AI models for personalisation, recommendation, and fraud detection
Provides practical knowledge for learners who aim to implement AI solutions in their applications
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How to Train Your AI Models at Scale.
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Career center
Learners who complete How to Train Your AI Models at Scale will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers are responsible for designing, developing, and deploying machine learning models. This course, How to Train Your AI Models at Scale, can help you develop the skills you need to be successful in this role. The course will teach you how to train and deploy machine learning models at scale, which is a critical skill for Machine Learning Engineers. Additionally, the course will provide you with a deep understanding of the Redis database, which is a popular choice for storing and managing machine learning data.
Data Scientist
Data Scientist
Data Scientists are responsible for collecting, analyzing, and interpreting data. This course, How to Train Your AI Models at Scale, can help you develop the skills you need to be successful in this role. The course will teach you how to train and deploy machine learning models at scale, which is a critical skill for Data Scientists. Additionally, the course will provide you with a deep understanding of the Redis database, which is a popular choice for storing and managing machine learning data.
Software Engineer
Software Engineer
Software Engineers are responsible for designing, developing, and maintaining software applications. This course, How to Train Your AI Models at Scale, can help you develop the skills you need to be successful in this role. The course will teach you how to train and deploy machine learning models at scale, which is a critical skill for Software Engineers. Additionally, the course will provide you with a deep understanding of the Redis database, which is a popular choice for storing and managing machine learning data.
Data Architect
Data Architect
Data Architects are responsible for designing and managing data systems. This course, How to Train Your AI Models at Scale, can help you develop the skills you need to be successful in this role. The course will teach you how to train and deploy machine learning models at scale, which is a critical skill for Data Architects. Additionally, the course will provide you with a deep understanding of the Redis database, which is a popular choice for storing and managing machine learning data.
Database Administrator
Database Administrator
Database Administrators are responsible for managing and maintaining databases. This course, How to Train Your AI Models at Scale, can help you develop the skills you need to be successful in this role. The course will teach you how to train and deploy machine learning models at scale, which is a critical skill for Database Administrators. Additionally, the course will provide you with a deep understanding of the Redis database, which is a popular choice for storing and managing machine learning data.
Solutions Architect
Solutions Architect
Solutions Architects are responsible for designing and implementing IT solutions. This course, How to Train Your AI Models at Scale, can help you develop the skills you need to be successful in this role. The course will teach you how to train and deploy machine learning models at scale, which is a critical skill for Solutions Architects. Additionally, the course will provide you with a deep understanding of the Redis database, which is a popular choice for storing and managing machine learning data.
Data Analyst
Data Analyst
Data Analysts are responsible for collecting, analyzing, and interpreting data. This course, How to Train Your AI Models at Scale, may be useful for you in this role. The course will teach you how to train and deploy machine learning models at scale, which is a valuable skill for Data Analysts. Additionally, the course will provide you with a deep understanding of the Redis database, which may be useful for storing and managing machine learning data.
Machine Learning Researcher
Machine Learning Researcher
Machine Learning Researchers are responsible for developing new machine learning algorithms and techniques. This course, How to Train Your AI Models at Scale, may be useful for you in this role. The course will teach you how to train and deploy machine learning models at scale, which is a valuable skill for Machine Learning Researchers. Additionally, the course will provide you with a deep understanding of the Redis database, which may be useful for storing and managing machine learning data.
Product Manager
Product Manager
Product Managers are responsible for managing the development and launch of new products. This course, How to Train Your AI Models at Scale, may be useful for you in this role. The course will teach you how to train and deploy machine learning models at scale, which is a valuable skill for Product Managers. Additionally, the course will provide you with a deep understanding of the Redis database, which may be useful for storing and managing product data.
Business Analyst
Business Analyst
Business Analysts are responsible for analyzing business processes and identifying areas for improvement. This course, How to Train Your AI Models at Scale, may be useful for you in this role. The course will teach you how to train and deploy machine learning models at scale, which is a valuable skill for Business Analysts. Additionally, the course will provide you with a deep understanding of the Redis database, which may be useful for storing and managing business data.
Cloud Architect
Cloud Architect
Cloud Architects are responsible for designing and implementing cloud computing solutions. This course, How to Train Your AI Models at Scale, may be useful for you in this role. The course will teach you how to train and deploy machine learning models at scale, which is a valuable skill for Cloud Architects. Additionally, the course will provide you with a deep understanding of the Redis database, which may be useful for storing and managing cloud data.
DevOps Engineer
DevOps Engineer
DevOps Engineers are responsible for bridging the gap between development and operations teams. This course, How to Train Your AI Models at Scale, may be useful for you in this role. The course will teach you how to train and deploy machine learning models at scale, which is a valuable skill for DevOps Engineers. Additionally, the course will provide you with a deep understanding of the Redis database, which may be useful for storing and managing DevOps data.
Data Engineer
Data Engineer
Data Engineers are responsible for designing and building data pipelines. This course, How to Train Your AI Models at Scale, may be useful for you in this role. The course will teach you how to train and deploy machine learning models at scale, which is a valuable skill for Data Engineers. Additionally, the course will provide you with a deep understanding of the Redis database, which may be useful for storing and managing data pipelines.
Big Data Engineer
Big Data Engineer
Big Data Engineers are responsible for designing and building big data systems. This course, How to Train Your AI Models at Scale, may be useful for you in this role. The course will teach you how to train and deploy machine learning models at scale, which is a valuable skill for Big Data Engineers. Additionally, the course will provide you with a deep understanding of the Redis database, which may be useful for storing and managing big data.
IT Consultant
IT Consultant
IT Consultants are responsible for providing IT advice and support to businesses. This course, How to Train Your AI Models at Scale, may be useful for you in this role. The course will teach you how to train and deploy machine learning models at scale, which is a valuable skill for IT Consultants. Additionally, the course will provide you with a deep understanding of the Redis database, which may be useful for storing and managing client data.
For more career information including salaries, visit:
OpenCourser.com/course/e9s4oy/how
Reading list
We've selected nine books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
How to Train Your AI Models at Scale.
Provides a collection of recipes for solving common problems with Redis. It covers a wide range of topics, from basic data manipulation to advanced techniques such as geospatial indexing and stream processing.
Provides a practical guide to machine learning using Python libraries such as Scikit-Learn, Keras, and TensorFlow. It covers a wide range of topics, including data preprocessing, model selection, and evaluation.
Provides a practical introduction to deep learning using the fastai library. It covers a wide range of topics, such as convolutional neural networks, recurrent neural networks, and transformers.
Provides a practical guide to building AI systems using Python. It covers the entire process of AI development, from data collection and preprocessing to model building and deployment.
Provides a comprehensive guide to DevOps. It covers the principles and practices of DevOps, as well as case studies from leading organizations.
Provides a comprehensive overview of the architectural patterns used in enterprise applications. It good reference for those who want to understand the design principles behind scalable and maintainable AI systems.
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Provides a practical guide to software architecture for developers. It covers topics such as software design principles, architectural patterns, and microservices.
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Provides a practical guide to continuous delivery. It covers the entire process of software delivery, from planning and development to testing and deployment.
Provides a gentle introduction to machine learning using Python. It covers the basics of machine learning, as well as more advanced topics such as neural networks and deep learning.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/e9s4oy/how
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Big Data LDN
This course belongs to a
collection
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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
- 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 (viewing)
- 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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