Overview: Welcome to the Big Data Analytics course with PySpark, Tableau Desktop, and MongoDB! This comprehensive course is designed to …
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Welcome to the Big Data Analytics course with PySpark, Tableau Desktop, and MongoDB! This comprehensive course is designed to equip you with the essential skills and knowledge required to excel in the field of big data analytics. In today’s data-driven world, the ability to analyze large datasets efficiently is a highly sought-after skill, and this course will provide you with a solid foundation to do just that.
The course begins with an introduction to big data analytics, where you will learn about the concepts and principles behind big data, its importance, and the challenges it presents. You will also gain an understanding of the various tools and technologies used in big data analytics, including PySpark, Tableau Desktop, and MongoDB.
Next, we will dive into PySpark, a powerful open-source framework for big data processing. You will learn how to set up a PySpark environment, work with RDDs (Resilient Distributed Datasets), and perform data transformations and actions using PySpark’s powerful APIs.
Following PySpark, we will explore Tableau Desktop, a leading data visualization tool. You will learn how to connect Tableau to different data sources, create interactive dashboards and visualizations, and share your insights with others.
Finally, we will cover MongoDB, a popular NoSQL database. You will learn how to install and configure MongoDB, perform CRUD (Create, Read, Update, Delete) operations, and work with MongoDB’s powerful aggregation framework.
By the end of this course, you will have gained the skills and knowledge needed to analyze large datasets using PySpark, visualize your insights using Tableau Desktop, and store and manage your data using MongoDB. Whether you are a beginner or an experienced professional, this course will help you take your big data analytics skills to the next level.
Upon completion of this course, you’ll acquire the following:
This course is designed for individuals interested in Big Data Analytics, including data scientists, analysts, and developers. It covers the basics of big data, data processing, analysis, and visualization. Students will learn how to use PySpark for distributed data processing, Tableau Desktop for data visualization, and MongoDB for NoSQL database management. The course includes hands-on exercises and projects to reinforce learning.
Participants should have a basic understanding of programming and data analysis. No prior experience with PySpark, Tableau Desktop, or MongoDB is required.
This course is ideal for data scientists, analysts, and developers interested in Big Data Analytics. It is suitable for individuals with basic knowledge of Python programming and familiarity with data analysis and visualization concepts.
Upon successful completion of the Blender 3D – Create a Cartoon Character course, learners can obtain both a PDF certificate and a Hard copy certificate for completely FREE. The Hard copy certificate is available for a nominal fee of £3.99, which covers the delivery charge within the United Kingdom. Additional delivery charges may apply for orders outside the United Kingdom.
An outstanding online course with clear explanations and practical examples. I could study at my own pace and still feel fully supported throughout. It’s truly boosted my confidence and career prospects
The course was well-structured, engaging, and easy to follow. The flexibility made it perfect alongside my full-time job. I’ve gained valuable, real-world skills that I can apply immediately.
Excellent learning experience from start to finish. The content was professional, up-to-date, and highly relevant. I would highly recommend it to anyone looking to upskill online.
| Section 01: Introduction | |||
| Introduction | 00:10:00 | ||
| Section 02: Setup and Installations | |||
| Python Installation | 00:03:00 | ||
| Installing Apache Spark | 00:12:00 | ||
| Installing Java (Optional) | 00:05:00 | ||
| Testing Apache Spark Installation | 00:06:00 | ||
| Installing MongoDB | 00:04:00 | ||
| Installing NoSQL Booster for MongoDB | 00:07:00 | ||
| Section 03: Data Processing with PySpark and MongoDB | |||
| Integrating PySpark with Jupyter Notebook | 00:05:00 | ||
| Data Extraction | 00:19:00 | ||
| Data Transformation | 00:15:00 | ||
| Loading Data into MongoDB | 00:13:00 | ||
| Section 04: Machine Learning with PySpark and MLlib | |||
| Data Pre-processing | 00:19:00 | ||
| Building the Predictive Model | 00:12:00 | ||
| Creating the Prediction Dataset | 00:08:00 | ||
| Section 05: Creating the Data Pipeline Scripts | |||
| Installing Visual Studio Code | 00:03:00 | ||
| Creating the PySpark ETL Script | 00:24:00 | ||
| Creating the Machine Learning Script | 00:27:00 | ||
| Section 06: Tableau Data Visualization | |||
| Installing Tableau | 00:02:00 | ||
| Installing MongoDB ODBC Drivers | 00:05:00 | ||
| Creating a System DSN for MongoDB | 00:05:00 | ||
| Loading the Data Sources | 00:06:00 | ||
| Creating a Geo Map | 00:13:00 | ||
| Creating a Bar Chart | 00:11:00 | ||
| Creating a Magnitude Chart | 00:13:00 | ||
| Creating a Table Plot | 00:04:00 | ||
| Creating a Dashboard | 00:06:00 | ||
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