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Knowledge engineers operate crucially in today’s data-driven landscape, overseeing pivotal tasks spanning knowledge ingestion, processing, transformation, and serving. As their expertise proves particularly valuable during the era of generative AI, where leveraging the value of massive datasets takes center stage.
To equip aspiring and experienced knowledge professionals, we have collaborated with leading organizations to introduce the ‘Skilled Certificates’, a cutting-edge series of credentials available on Coursera. This comprehensive program encompasses a range of knowledge engineering concepts, tools, and methodologies relevant to contemporary organizations. This resource is tailored to individuals possessing a certain level of proficiency in handling knowledge, who are eager to explore the fundamentals of knowledge engineering. The specialization comprises four hands-on programs, each concluding with the award of a Coursera course certificate upon successful completion.
This Knowledge Engineering Specialization is a collaborative effort between Amazon Web Services (AWS) and Coursera, the leading provider of high-quality artificial intelligence education founded by renowned machine learning expert Andrew Ng.
As a renowned expert in knowledge engineering and co-author of the best-selling e-book, Dr. [Name] spearheads this initiative as lead instructor. The curriculum establishes a comprehensive foundation by providing a holistic view of the information engineering lifecycle, thereby fostering learners’ understanding of crucial aspects such as knowledge structure, orchestration, DataOps, and knowledge management.
To further bolster its training prowess, this system offers immersive hands-on labs and technical evaluations seamlessly integrated within the Amazon Web Services (AWS) Cloud infrastructure. Sensible, cloud-based workout routines, co-designed with AWS technical consultants, cater to diverse fitness needs. Students will develop practical skills by leveraging theoretical concepts through hands-on experience with AWS tools and services such as Lambda, API Gateway, DynamoDB, and Rekognition.
Individual contributors have access to various key learning opportunities.
The specialization empowers knowledge engineers with the versatility to craft tailored solutions for diverse applications, select the most suitable technologies for their knowledge architecture, and proactively avoid potential obstacles. Acquired skills are universally transferable across multiple platforms and applied sciences, offering learners a flexible programme.
Unlike most programs focused on specific applied sciences, this specialisation provides a comprehensive grasp of knowledge engineering principles. Emphasizing the crucial importance of harmonizing knowledge engineering methodologies with overarching corporate objectives, this approach cultivates a more cohesive and effective framework for designing and maintaining knowledge solutions.
Through leveraging the key takeaways from the e-book, the curriculum delivers a comprehensive educational program that empowers professionals to excel in data-driven focused sectors.
AWS Companion’s hands-on labs enable learners to directly apply learned strategies within a controlled AWS environment provided as part of the course. Expertise in this domain is crucial for grasping the complexities of knowledge engineering and developing the skills required to thrive in the field.
- The specification is meticulously organized to provide a guided learning path, progressing seamlessly from core concepts to advanced capabilities.
- Glean valuable perspectives from the original authors as well as diverse industry experts. Construct a cutting-edge knowledge architecture on the cloud by leveraging cloud services to effectively integrate and analyze diverse datasets, fostering innovative insights and decision-making capabilities.
- Explore hands-on labs within the AWS Cloud where theory meets practice – learn by doing and apply your knowledge to real-world scenarios.
- This programme embodies the comprehensive scope of the information engineering lifecycle, incorporating knowledge generation through supply programmes, data ingestion, transformation, storage, and serving. This innovative endeavour further delves into the fundamental dynamics driving knowledge engineering, including crucial aspects such as ensuring safety, effectively governing and managing knowledge assets, and masterfully orchestrating these complex variables to achieve desired outcomes.
By the end of this specialization, learners will be thoroughly prepared with the necessary skills and practical experience to pursue a career in knowledge engineering, a highly sought-after role at the heart of any organization seeking to leverage knowledge to drive value creation. Knowledge-centric machine learning and analytics wouldn’t be possible without the muse of knowledge engineering.
The Knowledge Engineering Specialization comprises four distinct programs.
- This foundational module delves into the collaborative essence of knowledge engineering, identifying crucial stakeholders and grasping their requirements to foster a comprehensive understanding. The course explores the fundamental psychological principles of knowledge engineering, focusing on developing a comprehensive understanding of ecosystems, while also examining key factors such as knowledge quality, scalability, and effective requirement gathering. The course delves into the information engineering lifecycle, revealing intricate connections among various stages. By highlighting the capabilities of the AWS knowledge engineering stack, this course empowers learners to effectively leverage the relevant scientific disciplines. By the culmination of this course, learners will possess the skills and mental frameworks to tackle complex knowledge engineering obstacles and make informed decisions.
- Knowledge engineers embark on an in-depth exploration of the critical aspects involved in harnessing diverse knowledge sources, assimilating data through tailored ingestion strategies, and constructing robust pipelines that optimize insights and decision-making processes. Students uncover the characteristics of diverse information formats and suitable production tools for each type of content, empowering them to create effective information workflows by understanding how to efficiently design data streams. The course provides an introduction to both relational and NoSQL databases, exploring ACID compliance and CRUD operations to equip engineers with the skills necessary for working seamlessly with various data storage systems. The programme delves into the significance of cloud networking, optimising database connections, and leveraging message queues and real-time data streams – fundamental competencies for designing robust and highly available data structures. Through proficiently grasping the concepts on this course, knowledge engineers will be empowered to streamline knowledge intake procedures, enhance interconnectivity, and lay the groundwork for successful knowledge engineering projects, thereby driving business value.
- This course empowers knowledge engineers with innovative concepts and best practices for developing robust, eco-friendly knowledge repositories and query mechanisms. Students explore the concept of an information lake at home, building a medallion-like architecture by leveraging open desk formats to establish transactional knowledge lakes. The course boosts SQL expertise by teaching advanced query techniques, including aggregations and joins on real-time data, as well as delving into data warehouse and data lake functionalities? Students delve into the realm of data storage efficiency, discovering innovative techniques to streamline processes, including the application of indexing principles. Knowledge engineers can achieve optimal efficiency and scalability in knowledge provision by grasping the intricacies of question execution and processing mechanisms.
- On this comprehensive capstone course, knowledge engineers gain expertise in cutting-edge knowledge modeling techniques, leveraging powerful tools such as knowledge vaults and star schemas to optimize their skills. Students develop a nuanced understanding of contrasting data modeling methodologies, such as those proposed by Inmon and Kimball, thereby acquiring the agility to adapt their approach for optimal utilization in analytics and machine learning applications. The course empowers knowledge engineers to develop preprocessing skills for integrating textual, pictorial, and tabular data sets. Students recognize the differences between guided and self-directed learning, as well as classification and regression tasks, allowing them to create learning strategies that accommodate various forecasting capabilities. By grasping the fundamentals of knowledge modeling, transformation, and serving strategies, knowledge engineers can build robust, flexible, and commercially relevant knowledge frameworks to deliver maximum value.
Acquiring expertise in knowledge engineering, whether you’re a novice or seeking advancement, requires a harmonious blend of theoretical foundations and practical applications. This program offers a comprehensive approach, comprising four courses that conclude with the issuance of a Coursera course certificate.
Commence your foray into knowledge engineering from this very moment.
Upon completing all four programs, you’ll also receive the certificate.
Enroll now to kick-start your journey towards mastering knowledge engineering with our comprehensive program, built on a solid foundation and backed by Amazon Web Services (AWS).
