We may earn an affiliate commission when you visit our partners.
Big Data LDN
This course is no longer available. Find something similar by browsing:
Big Data
Analytics
Connected Car Ecosystem
Register for this course and see more details by visiting:
OpenCourser.com/course/mau3pa/introduction
Traffic lights
Traffic lights
Read about what's good
what should give you pause and
possible dealbreakers
Examines the interconnectedness of the automotive industry with other sectors, exploring the impact of data and analytics on the future of mobility
Taught by Big Data LDN, a recognized authority in the field of big data and analytics
Develops an understanding of the rapidly evolving technologies and trends that are shaping the connected car ecosystem
Provides a holistic overview of the connected car ecosystem, encompassing data collection, processing, analysis, and utilization
Features hands-on exercises and demonstrations that reinforce key concepts and enable practical application
Upon completion, learners will possess a comprehensive understanding of the connected car ecosystem and its implications for the automotive industry
Save this course
Create your own learning path.
Save this course to your list so you can find it easily later.
Save
Save
Activities
Coming soon
We're preparing activities for
Introduction to Adept and How Big Data and Analytics Is Transforming the Connected Car Ecosystem.
These are activities you can do either before, during, or after a course.
Career center
Learners who complete Introduction to Adept and How Big Data and Analytics Is Transforming the Connected Car Ecosystem will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts are responsible for collecting, cleaning, and interpreting data. They use this data to help businesses make better decisions. This course would be helpful for Data Analysts because it would provide them with the skills and knowledge needed to collect, clean, and interpret big data. Additionally, the course would help Data Analysts understand how big data is transforming the connected car ecosystem.
Data Engineer
Data Engineer
Data Engineers are responsible for designing and building the systems that store and process data. They work closely with Data Analysts to ensure that the data is accessible and usable. This course would be helpful for Data Engineers because it would provide them with the skills and knowledge needed to design and build systems that can store and process big data. Additionally, the course would help Data Engineers understand how big data is transforming the connected car ecosystem.
Data Scientist
Data Scientist
Data Scientists use data to solve business problems. They use a variety of techniques, including machine learning and statistical analysis, to extract insights from data. This course would be helpful for Data Scientists because it would provide them with the skills and knowledge needed to use big data to solve business problems. Additionally, the course would help Data Scientists understand how big data is transforming the connected car ecosystem.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers are responsible for building and deploying machine learning models. They work closely with Data Scientists to ensure that the models are accurate and reliable. This course would be helpful for Machine Learning Engineers because it would provide them with the skills and knowledge needed to build and deploy machine learning models that can use big data. Additionally, the course would help Machine Learning Engineers understand how big data is transforming the connected car ecosystem.
Software Engineer
Software Engineer
Software Engineers are responsible for designing, developing, and maintaining software applications. They work closely with Data Scientists and Machine Learning Engineers to ensure that the applications are able to use big data. This course would be helpful for Software Engineers because it would provide them with the skills and knowledge needed to design, develop, and maintain software applications that can use big data. Additionally, the course would help Software Engineers understand how big data is transforming the connected car ecosystem.
Product Manager
Product Manager
Product Managers are responsible for managing the development and launch of new products. They work closely with Data Scientists, Machine Learning Engineers, and Software Engineers to ensure that the products meet the needs of customers. This course would be helpful for Product Managers because it would provide them with the skills and knowledge needed to manage the development and launch of new products that use big data. Additionally, the course would help Product Managers understand how big data is transforming the connected car ecosystem.
Business Analyst
Business Analyst
Business Analysts are responsible for analyzing business needs and developing solutions to meet those needs. They work closely with Data Scientists, Machine Learning Engineers, and Software Engineers to ensure that the solutions are feasible and effective. This course would be helpful for Business Analysts because it would provide them with the skills and knowledge needed to analyze business needs and develop solutions that use big data. Additionally, the course would help Business Analysts understand how big data is transforming the connected car ecosystem.
Data Architect
Data Architect
Data Architects are responsible for designing and managing the data architecture of an organization. They work closely with Data Engineers and Data Scientists to ensure that the data architecture is scalable, reliable, and secure. This course would be helpful for Data Architects because it would provide them with the skills and knowledge needed to design and manage data architectures that can support big data. Additionally, the course would help Data Architects understand how big data is transforming the connected car ecosystem.
Data Governance Officer
Data Governance Officer
Data Governance Officers are responsible for developing and implementing data governance policies and procedures. They work closely with IT and legal counsel to ensure that the organization's data is used in a compliant and ethical manner. This course would be helpful for Data Governance Officers because it would provide them with the skills and knowledge needed to develop and implement data governance policies and procedures that are relevant to big data. Additionally, the course would help Data Governance Officers understand how big data is transforming the connected car ecosystem.
Data Privacy Officer
Data Privacy Officer
Data Privacy Officers are responsible for protecting the privacy of the organization's data. They work closely with IT and legal counsel to ensure that the organization is compliant with all applicable data privacy laws and regulations. This course would be helpful for Data Privacy Officers because it would provide them with the skills and knowledge needed to protect the privacy of big data. Additionally, the course would help Data Privacy Officers understand how big data is transforming the connected car ecosystem.
Data Security Officer
Data Security Officer
Data Security Officers are responsible for protecting the security of the organization's data. They work closely with IT and legal counsel to ensure that the organization is compliant with all applicable data security laws and regulations. This course would be helpful for Data Security Officers because it would provide them with the skills and knowledge needed to protect the security of big data. Additionally, the course would help Data Security Officers understand how big data is transforming the connected car ecosystem.
Automotive Engineer
Automotive Engineer
Automotive Engineers are responsible for designing, developing, and testing automobiles. They work closely with Data Scientists, Machine Learning Engineers, and Software Engineers to ensure that the автомобилей are safe, reliable, and efficient. This course would be helpful for Automotive Engineers because it would provide them with the skills and knowledge needed to design, develop, and test automobiles that use big data. Additionally, the course would help Automotive Engineers understand how big data is transforming the connected car ecosystem.
Transportation Planner
Transportation Planner
Transportation Planners are responsible for planning and managing transportation systems. They work closely with Data Scientists, Machine Learning Engineers, and Software Engineers to ensure that the transportation systems are efficient and effective. This course would be helpful for Transportation Planners because it would provide them with the skills and knowledge needed to plan and manage transportation systems that use big data. Additionally, the course would help Transportation Planners understand how big data is transforming the connected car ecosystem.
Urban Planner
Urban Planner
Urban Planners are responsible for planning and managing the development of cities and towns. They work closely with Data Scientists, Machine Learning Engineers, and Software Engineers to ensure that the development is sustainable and equitable. This course would be helpful for Urban Planners because it would provide them with the skills and knowledge needed to plan and manage the development of cities and towns that use big data. Additionally, the course would help Urban Planners understand how big data is transforming the connected car ecosystem.
Policy Analyst
Policy Analyst
Policy Analysts are responsible for developing and analyzing public policy. They work closely with Data Scientists, Machine Learning Engineers, and Software Engineers to ensure that the policy is based on evidence. This course would be helpful for Policy Analysts because it would provide them with the skills and knowledge needed to develop and analyze public policy that is based on big data. Additionally, the course would help Policy Analysts understand how big data is transforming the connected car ecosystem.
For more career information including salaries, visit:
OpenCourser.com/course/mau3pa/introduction
Reading list
We haven't picked any books for this reading list yet.
Provides a comprehensive guide to text processing with MapReduce, a framework for processing large datasets. It covers topics such as tokenization, stemming, and lemmatization, as well as more advanced topics such as sentiment analysis and text classification.
Save
Provides a technical overview of Big Data principles and best practices. It covers topics such as data ingestion, data storage, and data processing. It good option for those who want to gain a deeper understanding of the technical aspects of Big Data.
Save
Provides a comprehensive overview of deep learning, a subfield of machine learning that has revolutionized the field of artificial intelligence. It covers the fundamental concepts and algorithms of deep learning, as well as applications in various domains.
Covers the practical aspects of Big Data analytics, providing guidance on how to plan, implement, and integrate Big Data solutions in an enterprise environment. It includes discussions on NoSQL and graph databases, which are essential technologies for handling Big Data.
Provides an in-depth introduction to machine learning, covering the fundamental concepts and algorithms used in Big Data analysis. It is written by Andrew Ng, a leading expert in machine learning, and is highly recommended for those who want to gain a deeper understanding of Big Data.
Save
A reference for executives and policymakers who want to understand the implications of big data for the future of business and governance.
Introduces data science and its applications in business, covering topics such as data mining, data analysis, and machine learning. It provides a solid foundation for understanding the concepts and techniques involved in Big Data analysis.
Provides a comprehensive introduction to reinforcement learning, a type of machine learning that involves making decisions in order to maximize reward. It covers the fundamental concepts and algorithms of reinforcement learning, as well as applications in various domains.
Provides a comprehensive guide to Hadoop, the open-source framework for Big Data processing. It covers the core concepts and components of Hadoop, as well as advanced topics such as data warehousing and machine learning.
Save
Provides a practical introduction to data visualization, covering the principles and techniques involved in creating effective visualizations. It good option for those who want to learn how to visualize Big Data in order to communicate insights and make informed decisions.
Provides a comprehensive guide to Big Data analytics with Java, covering topics such as data ingestion, data storage, and data processing. It good option for those who want to gain a practical understanding of how to use Java to analyze Big Data.
Provides a comprehensive guide to Spark, the popular open-source framework for Big Data processing. It covers the core concepts and components of Spark, as well as advanced topics such as streaming data and machine learning.
Save
Provides an accessible introduction to the concepts and applications of predictive analytics. It uses engaging examples to illustrate how predictive models work and their impact across various industries. It's a good read for gaining a broad understanding of predictive analytics without delving into deep technical details.
Save
Provides practical guidance on how to use data analytics to solve real-world problems.
Provides a comprehensive overview of causal inference, which subfield of statistics that is used to determine the causal relationships between variables.
Provides a comprehensive overview of reinforcement learning, which subfield of machine learning.
Save
Provides a comprehensive overview of deep learning, which subfield of machine learning.
Provides a comprehensive overview of machine learning, which subfield of data analytics.
Is excellent for gaining a broad understanding of analytics, focusing on the fundamental principles of data science and the 'data-analytic thinking' necessary for extracting business value from data. It's commonly used as a textbook in MBA and analytics programs and provides a solid foundation for anyone looking to understand how analytics supports business decision-making.
Provides a comprehensive overview of the field of data analytics and is written in an easy-to-understand style.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/mau3pa/introduction
Share
Similar courses
Similar courses are unavailable at this time. Please try again later.
Via
Pluralsight
Instructor
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
- 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 (viewing)
- 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
Our mission
OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.
Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.
Find this site helpful? Tell a friend about us.
Affiliate disclosure
We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.
Your purchases help us maintain our catalog and keep our servers humming without ads.
Thank you for supporting OpenCourser.
© 2016 - 2025 OpenCourser