What are the system requirements PySpark Training Course?
You don’t have to worry about the system requirements as you will be executing your practicals on a Cloud LAB which is a pre-configured environment. This environment already contains all the necessary tools and services required for CertAdda’s PySpark Training.
How will I execute the practicals in this PySpark Certification Training?
You will execute all your PySpark Course Assignments/Case Studies in the Cloud LAB environment provided by CertAdda. You will be accessing the Cloud LAB via a browser. In case of any doubt, CertAdda’s Support Team will be available 24*7 for prompt assistance.
What is CloudLab?
CloudLab is a cloud-based Spark and Hadoop environment that CertAdda offers with the PySpark Training Course where you can execute all the in-class demos and work on real life spark case studies fluently. This will not only save you from the trouble of installing and maintaining Spark and Python on a virtual machine, but will also provide you an experience of a real big data and spark production cluster. You’ll be able to access the Spark Training CloudLab via your browser which requires minimal hardware configuration. In case, you get stuck in any step, our support team is ready to assist 24×7.
Which projects and case studies will be a part this CertAdda's PySpark Online Training Course?
At the end of the PySpark Training, you will be assigned with real-life use-cases as certification projects to further hone your skills and prepare you for the various Spark Developer Roles. Following are few industry-specific case studies that are included in our Apache Spark Developer Certification Training.
- Project 1- Domain: Financial
Statement: A leading financial bank is trying to broaden the financial inclusion for the unbanked population by providing a positive and safe borrowing experience. In order to make sure this underserved population has a positive loan experience, it makes use of a variety of alternative data–including telco and transactional information–to predict their clients’ repayment abilities. The bank has asked you to develop a solution to ensure that clients capable of repayment are not rejected and that loans are given with a principal, maturity, and repayment calendar that will empower their clients to be successful.
- Project 2- Domain: Transportation Industry
Business challenge/requirement: With the spike in pollution levels and the fuel prices, many Bicycle Sharing Programs are running around the world. Bicycle sharing systems are a means of renting bicycles where the process of obtaining membership, rental and bike return is automated via a network of joint locations throughout the city. Using this system people can rent a bike from one location and return it to a different place as and when needed.
Considerations: You are building a Bicycle Sharing demand forecasting service that combines historical usage patterns with weather data to forecast the Bicycle rental demand in real-time. To develop this system, you must first explore the dataset and build a model. Once it’s done you must persist the model and then on each request run a Spark job to load the model and make predictions on each Spark Streaming request
What if I miss a class?
You will never miss a lecture at CertAdda You can choose either of the two options: View the recorded session of the class available in your LMS or You can attend the missed session, in any other live batch.
What if I have queries after I complete this course?
Your access to the Support Team is for lifetime and will be available 24/7. The team will help you in resolving queries, during and after the course.
Will I get placement assistance?
To help you in this endeavor, we have added a resume builder tool in your LMS. Now, you will be able to create a winning resume in just 3 easy steps. You will have unlimited access to use these templates across different roles and designations. All you need to do is, log in to your LMS and click on the “create your resume” option.
Is the course material accessible to the students even after the course training is over?
Yes, the access to the course material will be available for lifetime once you have enrolled into the course.
Can I attend a demo session before enrollment?
We have limited number of participants in a live session to maintain the Quality Standards. So, unfortunately, participation in a live class without enrollment is not possible. However, you can go through the sample class recording and it would give you a clear insight into how are the classes conducted, quality of instructors and the level of interaction in a class.
Who are the instructors?
All the instructors at CertAdda are practitioners from the Industry with minimum 10-12 yrs of relevant IT experience. They are subject matter experts and are trained by CertAdda for providing an awesome learning experience to the participants.
What is PySpark?
Apache Spark is an open-source real-time in-memory cluster processing framework. It is used in streaming analytics systems such as bank fraud detection system, recommendation system, etc. Whereas Python is a general-purpose, high-level programming language. It has a wide-range of libraries which supports diverse types of applications. PySpark is a combination of Python and Spark. It provides Python API for Spark that lets you harness the simplicity of Python and the power of Apache Spark in order to tame Big Data.
What if I have more queries?
Just give us a CALL at +91 8178510474 / +91 9967920486 OR email at email@example.com
What is RDD in PySpark?
RDD stands for Resilient Distributed Dataset which is the building block of Apache Spark. RDD is fundamental data structure of Apache Spark which is an immutable distributed collection of objects. Each dataset in RDD is divided into logical partitions, which may be computed on different nodes of the cluster.
Is PySpark a language?
PySpark is not a language. PySpark is Python API for Apache Spark using which Python developers can leverage the power of Apache Spark and create in-memory processing applications. PySpark is developed to cater the huge amount of Python community.