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Boosting Your Chances for Landing a Job as a Data Scientist

Smart Data Collective

The number of data science jobs is expected to grow 36% between 2021 and 2031. Some of the top certificate programs include Certified Analytics Professional (CAP), Cloudera Data Platform Generalist Certification, Microsoft Certified: Azure Data Scientist Associate, and SAS Certified AI and Machine Learning Professional.

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Discover the Most Important Fundamentals of Data Engineering

Pickl AI

It involves developing data pipelines that efficiently transport data from various sources to storage solutions and analytical tools. OLAP (Online Analytical Processing): OLAP tools allow users to analyse data from multiple perspectives. billion by 2031, growing at a CAGR of 25.55% during the forecast period from 2024 to 2031.

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Know the Difference Between Cloud Computing and Grid Computing

Pickl AI

.” Instead of buying and maintaining expensive computer systems, you can rent the technology you need from cloud service providers like Amazon Web Services (AWS), Microsoft Azure, or Google Cloud. Yes, grid computing can benefit businesses that need to process massive data workloads, such as simulations or big data analytics.

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Must-Have Skills for a Machine Learning Engineer

Pickl AI

billion by 2031, growing at a CAGR of 34.20%. Cloud platforms like AWS , Google Cloud Platform (GCP), and Microsoft Azure provide managed services for Machine Learning, offering tools for model training, storage, and inference at scale. The global Machine Learning market was valued at USD 35.80

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Understanding and Building Machine Learning Models

Pickl AI

billion by 2031 at a CAGR of 34.20%. Predictive analytics uses historical data to forecast future trends, such as stock market movements or customer churn. Cloud Platforms for Machine Learning Cloud platforms like AWS, Google Cloud, and Microsoft Azure provide powerful infrastructures for building and deploying Machine Learning Models.

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Artificial intelligence as a service (AIaaS)

Dataconomy

Microsoft Azure AI: Provides a comprehensive suite of tools for data analysis and machine learning. SAS: Recognized for big data management and AI analytics capabilities. Projections indicate that the market could reach $273 billion by 2031, fueled by increasing demand for versatile AI applications across diverse industries.