Taking Your Spark MLlib Skills to the Next Level: Top 5 Intermediate Courses

Taking Your Spark MLlib Skills to the Next Level: Top 5 Intermediate Courses

Machine learning libraries are designed to relieve data scientists and engineers of the complexities surrounding data and aim on their data models. Spark MLib is one of those libraries. If you want to learn the Spark MLib and make a career with its help, this list article is something you need.


Introduction to Spark MLib

Spark MLlib is one of the machine learning libraries available in the market that comes with a simple design, is scalable and seamlessly assimilates with other tools. It consists of very common machine learning algorithms such as classification, regression, dimensionality, collaborative filtering, clustering etc. it provides a polished application programming interface for performing numerous machine learning tasks from clustering to regression to deep learning.

We have curated this list article, including top course providers and intermediate-level Spark MLib courses. Go through this and find out how to kickstart your career in this field and pick out the best course for you.?


Top Spark MLib Skills Required at Intermediate-Level

The Spark MLib skills that you need are as follows:

Clustering

Clustering is a necessary tool for Big Data Analytics. It is used either as a pre-processing step to reduce data dimensionality before running the learning algorithm or as a statistical tool to discover useful patterns within a dataset.??

SQL

It is important to know how to raw data into actionable insights and store it. To be an effective data engineer, you should know how to extract data from relational databases using SQL.


Top Spark MLib Learning Platforms

There are various learning platforms available for Spark MLib courses. Some of them are mentioned below.?

  • Coursera: It is a US-based online certification platform. It has partnered with 200+ universities and companies that provide flexible, affordable, job-relevant online learning to individuals and organizations worldwide.?
  • Talentedge: It is the first online platform to bring a ‘Live & Interactive’ online digital learning platform.


Spark MLib Courses

Machine Learning for Data Analysis by Coursera

  • This course by Coursera will teach you how to create, test, and implement predictive algorithms to achieve your goal of machine learning.
  • Pedagogy: This is an online self-paced course for 10 hours.
  • Instructor: This course is taught by Ms. Jen Rose and Ms. Lisa Dierker.
  • Practical Experience: This course includes case studies, instructor-moderated discussions and post-course interactions.?
  • Price: You can join this course for
  • ?1,691/month?
  • $21/month
  • £18/month


Linear Regression for Business Statistics by Coursera

  • This course by Coursera will teach you about Regression Analysis.
  • Pedagogy: This is an online self-paced course for 28 hours.
  • Instructor: This course is taught by Mr. Sharad Borle, Associate Professor of Management.
  • Practical Experience: This course includes case studies, instructor-moderated discussions and post-course interactions.?
  • Credibility: This course has received significant positive feedback and has a 5-star rating.
  • Price: You can join this course for
  • ?1,691/month?
  • $21/month
  • £18/month


Build a Machine Learning Web App with Streamlit and Python by Coursera

  • This course by Coursera will teach you how to build your first machine learning web application using the Streamlit Python library.?
  • Pedagogy: This is an online self-paced course for 1.5 hours.
  • Instructor: This course is taught by Mr. Snehan Kekre, a Documentation Writer at Streamlit.
  • Practical Experience: This course includes case studies, instructor-moderated discussions and post-course interactions. You will get to work on CapStone Project to ensure enhanced industry exposure.
  • Credibility: This course has received significant positive feedback and has a 4.5-star rating.
  • Price: You can join this course for
  • ?1,691/month?
  • $21/month
  • £18/month


Graduate Admission Prediction with Pyspark ML by Coursera

  • This course by Coursera will teach you how to create a linear regression model with PysparkML to predict student admission to the university.?
  • Pedagogy: This is an online self-paced course for 1.5 hours.
  • Instructor: This course is taught by Ms. Priya Jha, a Data Science instructor at Coursera.
  • Practical Experience: This course includes case studies, instructor-moderated discussions and post-course interactions. You will get to work on CapStone Project to ensure enhanced industry exposure.
  • Credibility: This course has received significant positive feedback and has a 5-star rating.
  • Price: You can join this course for
  • ?689?
  • $9
  • £7


Diabetes Prediction With Pyspark MLLIB by Coursera

  • This course by Coursera will teach you how to create a logistic regression model with PysparkMLLIB to classify patients either as diabetic or not.?
  • Pedagogy: This is an online self-paced course for 1.5 hours.
  • Instructor: This course is taught by Ms. Priya Jha, a Data Science instructor at Coursera.
  • Practical Experience: This course includes case studies, instructor-moderated discussions and post-course interactions. You will get to work on CapStone Project to ensure enhanced industry exposure.
  • Price: You can join this course for
  • ?689?
  • $9
  • £7


Final Thoughts

In this article, we explored the top five intermediate courses that can help you take your Spark MLlib skills to the next level. These courses cover a wide range of topics and provide in-depth knowledge and hands-on experience with Spark MLlib. Whether you want to learn advanced machine learning algorithms, enhance your data preprocessing and feature engineering skills, or dive deeper into Spark MLlib's optimization techniques, these courses offer valuable resources.

By enrolling in these intermediate courses, you can expand your knowledge and skills in Spark MLlib, making you better equipped to tackle complex machine learning projects at scale. Remember to practice what you learn and apply the concepts to real-world scenarios to solidify your understanding. Happy learning, and keep exploring the exciting world of Spark MLlib!

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