What you'll get
- 13+ Hours
- 6 Courses
- Mock Tests
- Course Completion Certificates
- Self-paced Courses
- Technical Support
- Case Studies
Synopsis
- Understand the fundamentals of PySpark and its ecosystem
- Perform data processing and analysis using Spark Python
- Work with big data concepts, Hadoop, and Spark APIs
- Build and manage data pipelines for large-scale datasets
- Apply real-time streaming techniques for data processing
- Implement analytics and predictive modeling using PySpark
- Gain hands-on experience with machine learning models in big data scenarios
- Enhance skills in Python, Java, or Scala for big data applications
Content
| Courses | No. of Hours | Certificates | Details |
|---|---|---|---|
| Pyspark Beginner | 2h 16m | ✔ | View Curriculum |
| Pyspark Intermediate | 2h 02m | ✔ | View Curriculum |
| Pyspark Advance | 1h 18m | ✔ | View Curriculum |
| Courses | No. of Hours | Certificates | Details |
|---|---|---|---|
| Apache Spark Fundamentals | 1h 38m | ✔ | View Curriculum |
| Apache Spark Advanced | 5h 47m | ✔ | View Curriculum |
| Project on Apache Spark: Building an ETL Framework | 2h 1m | ✔ | View Curriculum |
| Courses | No. of Hours | Certificates | Details |
|---|---|---|---|
| No courses found in this category. | |||
Description
The PySpark course provides a comprehensive introduction to Spark Python (PySpark), enabling learners to analyze large-scale datasets efficiently. This self-paced video course covers the core functionalities of PySpark, including data processing, analytics, and real-time streaming, all built on the Hadoop ecosystem.
Throughout the course, learners gain hands-on experience in building data pipelines, applying big data concepts, and leveraging PySpark for analytics and predictive modeling. This program targets developers, data engineers, analysts, and software professionals who want to enhance their big data processing and analytics skills using Python.
With lifetime access to the video lessons, verifiable completion certificates, and practical projects, this course equips learners with the skills required to manage, process, and analyze large datasets, preparing them for a successful career in big data and data analytics.
Sample Certificate
Requirements
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Basic knowledge of programming in Python, Java, Scala, or equivalent
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Understanding of big data concepts and the Hadoop ecosystem
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Familiarity with real-time data streaming and analytics
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Basic understanding of machine learning concepts is helpful
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A development background and willingness to work with large datasets.
Target Audience
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Developers, software engineers, and programmers interested in big data
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Data engineers and data analysts working with large-scale datasets
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Hadoop developers and big data professionals
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Students and entrepreneurs looking to build skills in PySpark and big data analytics
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Consultants and professionals aiming to enhance their expertise in data processing and predictive modeling.
