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Apache Spark (TM) SQL for Data Analysts (Coursera) https://www.coursera.org/learn/apache-spark-sql-for-data-analysts Apache Spark is one of the most widely used technologies in big data analytics. In this course, you will learn how to leverage your existing SQL skills to start working with Spark immediately. You will also learn how to work with Delta Lake, a highly performant, open-source storage layer that brings reliability to data lakes. By the end of this course, you will be able to use Spark SQL and Delta Lake to ingest, transform, and query data to extract valuable insights that can be shared with your t |
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Applied Data Science for Data Analysts (Coursera) https://www.coursera.org/learn/applied-data-science-for-data-analysts In this course, you will develop your data science skills while solving real-world problems. You'll work through the data science process to and use unsupervised learning to explore data, engineer and select meaningful features, and solve complex supervised learning problems using tree-based models. You will also learn to apply hyperparameter tuning and cross-validation strategies to improve model performance. NOTE: This is the third and final course in the Data Science with Databricks for Data |
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Bayesian Inference with MCMC (Coursera) https://www.coursera.org/learn/mcmc The objective of this course is to introduce Markov Chain Monte Carlo Methods for Bayesian modeling and inference, The attendees will start off by learning the the basics of Monte Carlo methods. This will be augmented by hands-on examples in Python that will be used to illustrate how these algorithms work. This will be the second course in a specialization of three courses .Python and Jupyter notebooks will be used throughout this course to illustrate and perform Bayesian modeling with PyMC3. T |
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Data Science Fundamentals for Data Analysts (Coursera) https://www.coursera.org/learn/data-science-fundamentals-for-data-analysts In this course we're going to guide you through the fundamental building blocks of data science, one of the fastest-growing fields in the world! With the help of our industry-leading data scientists, we’ve designed this course to build ready-to-apply data science skills in just 15 hours of learning. First, we’ll give you a quick introduction to data science - what it is and how it is used to solve real-world problems. For the rest of the course, we'll teach you the skills you need to apply fou |
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Data Science with Databricks for Data Analysts (CourseraSpecs) https://www.coursera.org/specializations/data-science-with-databricks-for-data-analysts Offered by Databricks. |
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Introduction to Bayesian Statistics (Coursera) https://www.coursera.org/learn/compstatsintro The objective of this course is to introduce Computational Statistics to aspiring or new data scientists. The attendees will start off by learning the basics of probability, Bayesian modeling and inference. This will be the first course in a specialization of three courses .Python and Jupyter notebooks will be used throughout this course to illustrate and perform Bayesian modeling. The course website is located at https://sjster.github.io/introduction_to_computational_statistics/docs/index.html. |
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Introduction to Computational Statistics for Data Scientists (CourseraSpecs) https://www.coursera.org/specializations/compstats Offered by Databricks. Practical Bayesian Inference. A conceptual understanding of the techniques and the tools used to perform scalable ... |
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Introduction to PyMC3 for Bayesian Modeling and Inference (Coursera) https://www.coursera.org/learn/introduction-to-pymc3 The objective of this course is to introduce PyMC3 for Bayesian Modeling and Inference, The attendees will start off by learning the the basics of PyMC3 and learn how to perform scalable inference for a variety of problems. This will be the final course in a specialization of three courses .Python and Jupyter notebooks will be used throughout this course to illustrate and perform Bayesian modeling with PyMC3.. The course website is located at https://sjster.github.io/introduction_to_computation |