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Do you want to start a career in cloud computing, but don't know where to begin? If so, this course can help by providing an ideal foundational mapping of the career paths and certifications that IT professionals should consider if they're interested in transitioning to cloud computing. Instructor and cloud architect Lynn Langit covers a variety of career paths, including IT pro, developer, analyst, and architect roles. Throughout the course, she focuses on the major cloud platforms—AWS, Microsoft Azure, Google, and Alibaba—discusses certifications available for each, and explores the future of cloud computing careers.
CEO Lynn Langit Consulting LLCLynn Langit is a cloud architect who works with Amazon Web Services and Google Cloud Platform.
Lynn specializes in big data projects. She has worked with AWS Athena, Aurora, Redshift, Kinesis, and the IoT. She has also done production work with Databricks for Apache Spark and Google Cloud Dataproc, Bigtable, BigQuery, and Cloud Spanner.
Lynn is also the cofounder of Teaching Kids Programming. She has spoken on data and cloud technologies in North and South America, Europe, Africa, Asia, and Australia.
Skills covered in this course
For each course you will get
- Exercise files and quizzes
- Certificate of completion from LinkedIn
- Offline and audio-only options
Moving towards the cloud“
- [Instructor] So the next role to map from on-prem to Cloud skills is analyst. And this is pretty broad, it can be everything from a business analyst who's doing business analytics or reporting whether on spreadsheets or from a database to a statistician or a data scientist who's doing predictive analytics on some subset of enterprise data. Now the really hot area here is machine learning developer. And again, it's funny how names change so quickly and kind of mean the same thing. When I first was moving into Cloud work, data scientist was how applied statistics on the Cloud was called as a role. And I've really seen over the past, really actually year or so, that data scientist has become machine learning developer. Now interestingly, that means someone who understands statistics but increasingly it also means someone who understands how to write code. So it becomes kind of a joining of application developer and a person who has data science skills. Sort of a relatively new career…
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