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Big Data LDN
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Multiparadigm Data Science
Decision Making
Big Data
Symbolic Computation
Computable Data
Notebook Interfaces
Automated AI
Register for this course and see more details by visiting:
OpenCourser.com/course/meyawm/multiparadigm
Traffic lights
Traffic lights
Read about what's good
what should give you pause and
possible dealbreakers
Strengthens an existing foundation for intermediate learners who ask, "Has 'Big Data' led to better decisions at your organisation?"
Explores topics, which is not taught in many other places
Taught by Big Data LDN, who are recognized for their work in the field of data analysis
Offers hands-on labs and interactive materials to help learners apply what they learn
Requires learners to come in with extensive background knowledge, which may be a barrier for some
May be outdated if latest versions of the software are released during the course
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Activities
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We're preparing activities for
Multiparadigm Data Science: The Next Frontier in Decision Making.
These are activities you can do either before, during, or after a course.
Career center
Learners who complete Multiparadigm Data Science: The Next Frontier in Decision Making will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists are responsible for developing and implementing machine learning models. They use their knowledge of mathematics, statistics, and computer science to build models that can predict future events or identify patterns in data. The Multiparadigm Data Science course can help Data Scientists learn the latest techniques in machine learning and AI. The course will also teach students how to use the Wolfram Technology stack to build and deploy their models.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers are responsible for building and maintaining machine learning systems. They work with Data Scientists to develop and implement models, and they also work with software engineers to deploy and scale these models. The Multiparadigm Data Science course can help Machine Learning Engineers learn the latest techniques in machine learning and AI. The course will also teach students how to use the Wolfram Technology stack to build and deploy their models.
Data Analyst
Data Analyst
Data Analysts are responsible for collecting, cleaning, and making sense of data. They use their analytical skills to identify trends and patterns, and they develop visualizations to communicate their findings to stakeholders. The Multiparadigm Data Science course can help Data Analysts build a solid foundation in data analysis techniques. The course will also teach students how to use the Wolfram Technology stack to automate their workflows and accelerate their insights.
Data Engineer
Data Engineer
Data Engineers build and maintain data pipelines. They work with data scientists and software engineers to develop and implement solutions that meet the data needs of an organization. The Multiparadigm Data Science course can help Data Engineers learn the latest techniques in data engineering. The course will also teach students how to use the Wolfram Technology stack to build and deploy their pipelines.
Statistician
Statistician
Statisticians collect, analyze, and interpret data. They use their knowledge of mathematics and statistics to develop models that can predict future events or identify patterns in data. The Multiparadigm Data Science course can help Statisticians learn the latest techniques in data analysis and machine learning. The course will also teach students how to use the Wolfram Technology stack to automate their workflows and accelerate their insights.
Fraud Analyst
Fraud Analyst
Fraud Analysts investigate and prevent fraud. They use their knowledge of fraud detection and data analysis to identify suspicious activity. The Multiparadigm Data Science course can help Fraud Analysts learn the latest techniques in data analysis and machine learning. The course will also teach students how to use the Wolfram Technology stack to automate their workflows and accelerate their insights.
Actuary
Actuary
Actuaries use mathematical and statistical models to assess risk and uncertainty. They use their findings to develop insurance policies and other financial products. The Multiparadigm Data Science course can help Actuaries learn the latest techniques in data analysis and machine learning. The course will also teach students how to use the Wolfram Technology stack to automate their workflows and accelerate their insights.
Software Engineer
Software Engineer
Software Engineers develop and maintain software applications. They work with a variety of technologies, including programming languages, databases, and operating systems. The Multiparadigm Data Science course can help Software Engineers build a foundation in data analysis and machine learning. The course will also teach students how to use the Wolfram Technology stack to build and deploy their applications.
Data Architect
Data Architect
Data Architects design and build data architectures. They work with stakeholders to understand their data needs, and they develop solutions that meet those needs. The Multiparadigm Data Science course can help Data Architects learn the latest techniques in data management and data integration. The course will also teach students how to use the Wolfram Technology stack to build and deploy their architectures.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data. They use their findings to make recommendations on investment decisions. The Multiparadigm Data Science course can help Quantitative Analysts learn the latest techniques in data analysis and machine learning. The course will also teach students how to use the Wolfram Technology stack to automate their workflows and accelerate their insights.
Risk Analyst
Risk Analyst
Risk Analysts identify and assess risks to an organization. They use their knowledge of risk management and data analysis to develop strategies to mitigate these risks. The Multiparadigm Data Science course can help Risk Analysts learn the latest techniques in data analysis and machine learning. The course will also teach students how to use the Wolfram Technology stack to automate their workflows and accelerate their insights.
Business Analyst
Business Analyst
Business Analysts analyze business processes and develop solutions to improve them. They use their knowledge of business and technology to identify problems and opportunities, and they develop recommendations for how to address them. The Multiparadigm Data Science course can help Business Analysts build a foundation in data analysis and machine learning. The course will also teach students how to use the Wolfram Technology stack to automate their workflows and accelerate their insights.
For more career information including salaries, visit:
OpenCourser.com/course/meyawm/multiparadigm
Reading list
We've selected eight 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
Multiparadigm Data Science: The Next Frontier in Decision Making.
Provides a comprehensive introduction to deep learning with Python. It covers the key concepts, tools, and techniques.
Provides a comprehensive overview of big data analytics, covering the key concepts, tools, and techniques. It valuable resource for anyone who wants to learn more about this important field.
Provides a comprehensive introduction to natural language processing for beginners. It covers the key concepts, tools, and techniques in a clear and concise way.
Provides a comprehensive introduction to natural language processing with Python. It covers the key concepts, tools, and techniques.
Provides a practical introduction to data science for business professionals. It covers the key concepts and techniques of data mining and data-analytic thinking.
Provides a comprehensive introduction to machine learning with Python. It covers the key concepts, tools, and techniques.
Provides a comprehensive introduction to big data analytics for business professionals. It covers the key concepts, tools, and techniques.
Provides a comprehensive introduction to data analytics for beginners. It covers the key concepts, tools, and techniques.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/meyawm/multiparadigm
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This course belongs to a
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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 (viewing)
- 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
- 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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