Implementing Predictive Analytics with Spark in Azure HDInsight
This course teaches how to use Apache Spark and Microsoft Azure HDInsight to create predictive analytics solutions for big data. Learners will gain experience with Scala and Python to cleanse and transform data, build machine learning models, and deploy them in production. ▼
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Course Feature
Cost:
Free
Provider:
Edx
Certificate:
No Information
Language:
English
Start Date:
1st Oct, 2019
Course Overview
❗The content presented here is sourced directly from Edx platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.
Updated in [March 06th, 2023]
This course, Implementing Predictive Analytics with Spark in Azure HDInsight, provides learners with the opportunity to learn how to implement predictive analytics solutions for big data using Apache Spark in Microsoft Azure HDInsight. Learners will gain an understanding of how to work with Scala or Python to cleanse and transform data and build machine learning models with Spark ML (the machine learning library in Spark). In order to complete the hands-on elements of this course, learners will require an Azure subscription and a Windows client computer. Those who do not have an Azure subscription can sign up for a free Azure trial subscription (a valid credit card is required for verification, but learners will not be charged for Azure services). Note that the free trial is not available in all regions. Additionally, edX offers financial assistance for learners who want to earn Verified Certificates but who may not be able to pay the fee. To apply for financial assistance, learners must enroll in the course and then follow the provided link to complete an application for assistance.
[Applications]
After completing this course, learners can apply their knowledge of predictive analytics with Spark in Azure HDInsight to develop and deploy machine learning models. Learners can also use the skills they have acquired to cleanse and transform data, and to build and evaluate machine learning models. Additionally, learners can use the knowledge they have gained to apply for financial assistance to earn a Verified Certificate.
[Career Paths]
1. Data Scientist: Data Scientists are responsible for analyzing large datasets to uncover trends and insights. They use a variety of tools and techniques, such as machine learning, to develop predictive models and uncover patterns in data. Data Scientists are in high demand, and the demand is expected to continue to grow as more organizations adopt big data technologies.
2. Big Data Engineer: Big Data Engineers are responsible for designing, developing, and maintaining big data systems. They use a variety of technologies, such as Apache Spark, to process and analyze large datasets. Big Data Engineers are in high demand, and the demand is expected to continue to grow as more organizations adopt big data technologies.
3. Machine Learning Engineer: Machine Learning Engineers are responsible for developing and deploying machine learning models. They use a variety of tools and techniques, such as Apache Spark, to build and deploy predictive models. Machine Learning Engineers are in high demand, and the demand is expected to continue to grow as more organizations adopt big data technologies.
4. Cloud Architect: Cloud Architects are responsible for designing and implementing cloud-based solutions. They use a variety of technologies, such as Microsoft Azure, to build and deploy cloud-based applications. Cloud Architects are in high demand, and the demand is expected to continue to grow as more organizations adopt cloud-based technologies.
[Education Paths]
1. Bachelor of Science in Data Science: A Bachelor of Science in Data Science is a degree program that focuses on the application of data science principles and techniques to solve real-world problems. This degree program typically includes courses in mathematics, statistics, computer science, and data analysis. It also covers topics such as machine learning, artificial intelligence, and data visualization. This degree is becoming increasingly popular as businesses and organizations recognize the value of data-driven decision-making.
2. Master of Science in Data Science: A Master of Science in Data Science is a degree program that focuses on the application of data science principles and techniques to solve real-world problems. This degree program typically includes courses in mathematics, statistics, computer science, and data analysis. It also covers topics such as machine learning, artificial intelligence, and data visualization. This degree is becoming increasingly popular as businesses and organizations recognize the value of data-driven decision-making.
3. Doctor of Philosophy in Data Science: A Doctor of Philosophy in Data Science is a degree program that focuses on the application of data science principles and techniques to solve real-world problems. This degree program typically includes courses in mathematics, statistics, computer science, and data analysis. It also covers topics such as machine learning, artificial intelligence, and data visualization. This degree is becoming increasingly popular as businesses and organizations recognize the value of data-driven decision-making.
4. Master of Business Administration in Data Science: A Master of Business Administration in Data Science is a degree program that focuses on the application of data science principles and techniques to solve real-world problems. This degree program typically includes courses in mathematics, statistics, computer science, and data analysis. It also covers topics such as machine learning, artificial intelligence, and data visualization. This degree is becoming increasingly popular as businesses and organizations recognize the value of data-driven decision-making.
Course Provider
Provider Edx's Stats at AZClass
Implementing Predictive Analytics with Spark in Azure HDInsight teaches how to create predictive analytics solutions for big data using Apache Spark and Microsoft Azure HDInsight. Learners can learn how to use Apache Spark in Microsoft Azure HDInsight to implement big data predictive analysis solutions. This course will teach learners how to clean and transform data using Scala or Python, and build machine learning models using Spark ML, the machine learning library in Spark. Learners will also understand the fundamentals of cloud computing and big data, and how they can be used to create predictive analytics solutions.
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