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7 Free Google Cloud Training Resources

ParkMyCloud

If you’re looking to break into the cloud computing space, or just continue growing your skills and knowledge, there are an abundance of resources out there to help you get started, including free Google Cloud training. Google Cloud Free Program. GCP’s free program option is a no-brainer thanks to its offerings. .

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The 10 most in-demand IT jobs in finance

CIO

The most in-demand skills include DevOps, Java, Python, SQL, NoSQL, React, Google Cloud, Microsoft Azure, and AWS tools, among others. The average salary for a full stack software engineer is $115,818 per year, with a reported salary range of $85,000 to $171,000 per year, according to data from Glassdoor. Data engineer.

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The 10 most in-demand IT jobs in finance

CIO

The most in-demand skills include DevOps, Java, Python, SQL, NoSQL, React, Google Cloud, Microsoft Azure, and AWS tools, among others. The average salary for a full stack software engineer is $115,818 per year, with a reported salary range of $85,000 to $171,000 per year, according to data from Glassdoor. Data engineer.

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What is Data Engineering: Explaining Data Pipeline, Data Warehouse, and Data Engineer Role

Altexsoft

However, they often forget about the fundamental work – data literacy, collection, and infrastructure – that must be done prior to building intelligent data products. This discipline is not to be underestimated, as it enables effective data storing and reliable data flow while taking charge of the infrastructure.

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Equalum lands new capital to help companies build data pipelines

TechCrunch

In a recent MuleSoft survey , 84% of organizations said that data and app integration challenges were hindering their digital transformations and, by extension, their adoption of cloud platforms. Equalum manages data pipelines, leveraging open source packages, including Apache Spark and Kafka to stream and batch data processes.

Company 191
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Should you build or buy generative AI?

CIO

A general LLM won’t be calibrated for that, but you can recalibrate it—a process known as fine-tuning—to your own data. Fine-tuning applies to both hosted cloud LLMs and open source LLM models you run yourself, so this level of ‘shaping’ doesn’t commit you to one approach.

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Demystifying MLOps: From Notebook to ML Application

Xebia

Data science is generally not operationalized Consider a data flow from a machine or process, all the way to an end-user. 2 In general, the flow of data from machine to the data engineer (1) is well operationalized. You could argue the same about the data engineering step (2) , although this differs per company.