2 mins to read Machine Learning with Apache Spark
Explore the exciting world of machine learning with this IBM course.
Start by learning ML fundamentals before unlocking the power of Apache Spark to build and deploy ML models for data engineering applications. Dive into supervised and unsupervised learning techniques and discover the revolutionary possibilities of Generative AI through instructional readings and videos. Gain hands-on experience with Spark structured streaming, develop an understanding of data engineering and ML pipelines, and become proficient in evaluating ML models using SparkML.
Build your subject-matter expertise: Machine Learning with Apache Spark
This Machine Learning with Apache Spark is available as part of program
When you enroll in this course, you’ll also be asked to select a specific program.
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate
What you’ll learn: Machine Learning with Apache Spark
- Describe ML, explain its role in data engineering, summarize generative AI, discuss Spark’s uses, and analyze ML pipelines and model persistence.
- Evaluate ML models, distinguish between regression, classification, and clustering models, and compare data engineering pipelines with ML pipelines.
- Construct the data analysis processes using Spark SQL, and perform regression, classification, and clustering using SparkML.
- Demonstrate connecting to Spark clusters, build ML pipelines, perform feature extraction and transformation, and model persistence.
How to Enroll: Machine Learning with Apache Spark
- Choose your desired certificate program on the IBM website.
- Create an IBM ID if you don’t have one.
- Select specific courses within your chosen program.
- Enroll in courses, and pay if necessary.
- Access course materials and complete requirements.
- Prepare for and take certification exams if required.
- Earn your certificate upon successful completion.
- Be aware of maintenance or renewal requirements, if applicable.