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AWS Projects

AWS Project for Batch Processing with PySpark on AWS EMR

In this AWS Project, you will learn how to perform batch processing on Wikipedia data with PySpark on AWS EMR.

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Build an AWS ETL Data Pipeline in Python on YouTube Data

AWS Project - Learn how to build ETL Data Pipeline in Python on YouTube Data using Athena, Glue and Lambda

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Build a Real-Time Spark Streaming Pipeline on AWS using Scala

In this Spark Streaming project, you will build a real-time spark streaming pipeline on AWS using Scala and Python.

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AWS Project-Website Monitoring using AWS Lambda and Aurora

In this AWS Project, you will learn the best practices for website monitoring using AWS services like Lambda, Aurora MySQL, Amazon Dynamo DB and Kinesis.

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Graph Database Modelling using AWS Neptune and Gremlin

In this data analytics project, you will use AWS Neptune graph database and Gremlin query language to analyse various performance metrics of flights.

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Orchestrate Redshift ETL using AWS Glue and Step Functions

ETL Orchestration on AWS - Use AWS Glue and Step Functions to fetch source data and glean faster analytical insights on Amazon Redshift Cluster

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Building Real-Time AWS Log Analytics Solution

In this AWS Project, you will build an end-to-end log analytics solution to collect, ingest and process data. The processed data can be analysed to monitor the health of production systems on AWS.

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COVID-19 Data Analysis Project using Python and AWS Stack

COVID-19 Data Analysis Project using Python and AWS to build an automated data pipeline that processes COVID-19 data from Johns Hopkins University and generates interactive dashboards to provide insights into the pandemic for public health officials, researchers, and the general public.

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dbt Snowflake Project to Master dbt Fundamentals in Snowflake

DBT Snowflake Project to Master the Fundamentals of DBT and learn how it can be used to build efficient and robust data pipelines with Snowflake.

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Build an ETL Pipeline with DBT, Snowflake and Airflow

Data Engineering Project to Build an ETL pipeline using technologies like dbt, Snowflake, and Airflow, ensuring seamless data extraction, transformation, and loading, with efficient monitoring through Slack and email notifications via SNS

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AWS CDK and IoT Core for Migrating IoT-Based Data to AWS

Learn how to use AWS CDK and various AWS services to replicate an On-Premise Data Center infrastructure by ingesting real-time IoT-based.

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How to deal with slowly changing dimensions using snowflake?

Implement Slowly Changing Dimensions using Snowflake Method - Build Type 1 and Type 2 SCD in Snowflake using the Stream and Task Functionalities

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PySpark Project-Build a Data Pipeline using Kafka and Redshift

In this PySpark ETL Project, you will learn to build a data pipeline and perform ETL operations by integrating PySpark with Apache Kafka and AWS Redshift

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EMR Serverless Example to Build a Search Engine for COVID19

In this AWS Project, create a search engine using the BM25 TF-IDF Algorithm that uses EMR Serverless for ad-hoc processing of a large amount of unstructured textual data.

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AWS Snowflake Data Pipeline Example using Kinesis and Airflow

Learn to build a Snowflake Data Pipeline starting from the EC2 logs to storage in Snowflake and S3 post-transformation and processing through Airflow DAGs

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Getting Started with Pyspark on AWS EMR and Athena

In this AWS Big Data Project, you will learn to perform Spark Transformations using a real-time currency ticker API and load the processed data to Athena using Glue Crawler.

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Build Serverless Pipeline using AWS CDK and Lambda in Python

In this AWS Data Engineering Project, you will learn to build a serverless pipeline using AWS CDK and other AWS serverless technologies like AWS Lambda and Glue.

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Hadoop Project-Analysis of Yelp Dataset using Hadoop Hive

The goal of this hadoop project is to apply some data engineering principles to Yelp Dataset in the areas of processing, storage, and retrieval.

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Snowflake Real Time Data Warehouse Project for Beginners-1

In this Snowflake Data Warehousing Project, you will learn to implement the Snowflake architecture and build a data warehouse in the cloud to deliver business value.

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Streaming Data Pipeline using Spark, HBase and Phoenix

Build a Real-Time Streaming Data Pipeline for an application that monitors oil wells using Apache Spark, HBase and Apache Phoenix .

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Build a real-time Streaming Data Pipeline using Flink and Kinesis

In this big data project on AWS, you will learn how to run an Apache Flink Python application for a real-time streaming platform using Amazon Kinesis.

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Build an Analytical Platform for eCommerce using AWS Services

In this AWS Big Data Project, you will use an eCommerce dataset to simulate the logs of user purchases, product views, cart history, and the user’s journey to build batch and real-time pipelines.

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Learn Efficient Multi-Source Data Processing with Talend ETL

In this Talend ETL Project , you will create a multi-source ETL Pipeline to load data from multiple sources such as MySQL Database, Azure Database, and API to Snowflake cloud using Talend Jobs.

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Python and MongoDB Project for Beginners with Source Code-Part 1

In this Python and MongoDB Project, you learn to do data analysis using PyMongo on MongoDB Atlas Cluster.

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AWS CDK Project for Building Real-Time IoT Infrastructure

AWS CDK Project for Beginners to Build Real-Time IoT Infrastructure and migrate and analyze data to

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Migration of MySQL Databases to Cloud AWS using AWS DMS

IoT-based Data Migration Project using AWS DMS and Aurora Postgres aims to migrate real-time IoT-based data from an MySQL database to the AWS cloud.

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Build an ETL Pipeline on EMR using AWS CDK and Power BI

In this ETL Project, you will learn build an ETL Pipeline on Amazon EMR with AWS CDK and Apache Hive. You'll deploy the pipeline using S3, Cloud9, and EMR, and then use Power BI to create dynamic visualizations of your transformed data.

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Build a Streaming Pipeline with DBT, Snowflake and Kinesis

This dbt project focuses on building a streaming pipeline integrating dbt Cloud, Snowflake and Amazon Kinesis for real-time processing and analysis of Stock Market Data.

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Python and MongoDB Project for Beginners with Source Code-Part 2

In this Python and MongoDB Project for Beginners, you will learn how to use Apache Sedona and perform advanced analysis on the Transportation dataset.

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Build an Incremental ETL Pipeline with AWS CDK

Learn how to build an Incremental ETL Pipeline with AWS CDK using Cryptocurrency data

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Customer Love

As a student looking to break into the field of data engineering and data science, one can get really confused as to which path to take. Very few ways to do it are Google, YouTube, etc. I was one of them too, and that's when I came across ProjectPro while watching one of the SQL videos on the E-Learning Bridge YouTube channel. One of the standout features was that it featured real projects on topics I just read about, across different job descriptions at the time. The main issue was the right path to guide us in using these tools and adding to the resume, and that's exactly what ProjectPro got me through. The fact that I can have a reliable route and videos explaining each tool in detail really motivated me to continue with the platform. Another thing we all struggle with is how to really connect with someone if we're stuck somewhere because there are so many solutions. But this has also been solved by experts we can chat with and believe me when I say this they will do whatever it takes to solve your problem even if it takes longer than expected. In my sophomore year of college and getting hands-on exposure to technologies like PySpark, NLP, Kafka, etc, and being able to really apply the theory and work on a project from start to finish really boosted my confidence in general!

Savvy Sahai

Data Science Intern, Capgemini

Having worked in the field of Data Science, I wanted to explore how I can implement projects in other domains, So I thought of connecting with ProjectPro. A project that helped me absorb this topic was "Credit Risk Modelling". To understand other domains, it is important to wear a thinking cap and that's where ProjectPro helped me. I also got a chance to talk to experts who have worked on these domains - they helped me by walking through the project. Kudos to the ProjectPro team!

Gautam Vermani

Data Consultant at Confidential

I come from a background in Marketing and Analytics and when I developed an interest in Machine Learning algorithms, I did multiple in-class courses from reputed institutions though I got good theoretical knowledge, the practical approach, real word application, and deployment knowledge were missing. ProjectPro helped me bridge that gap. ProjectPro has real-time projects that helped me improve my skills. What I liked most is that I get exposure to so many projects, given the work nature I wouldn't have gotten exposure to such a variety of projects and their approaches. It is helping me apply knowledge to other projects too. I highly recommend ProjectPro to everyone who wants to excel in their DataScience career.

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ETL (Abintio) developer at IBM

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Abhinav Agarwal

Graduate Student at Northwestern University

I think that they are fantastic. I attended Yale and Stanford and have worked at Honeywell,Oracle, and Arthur Andersen(Accenture) in the US. I have taken Big Data and Hadoop,NoSQL, Spark, Hadoop Admin, Hadoop projects. I have been happy with every project. They have really brought me into the forefront of Data Science and Big data. I would recommend this to everyone. It is more than worth the price. After working with them I feel so much more employable for current projects.

Ray han

Tech Leader | Stanford / Yale University

I am the Director of Data Analytics with over 10+ years of IT experience. I have a background in SQL, Python, and Big Data working with Accenture, IBM, and Infosys. I am looking to enhance my skills in Data Engineering/Science and hoping to find real-world projects fortunately, I came across Project Pro. Project Pro helped me by providing an in-depth explanation of the end-to-end real-world data engineering projects. From data extraction, transformation, and storage up to data visualization. I learned more about Kafka, AWS, NI-FI, and Spark. Thru the help of the knowledge I gained from Project Pro, I was able to do well in the coding exams, interview and helped me land a job at EY. I will recommend every aspiring data professional as well as existing data science/engineer expert to try Project Pro to enhance their knowledge.

Ed Godalle

Director Data Analytics at EY / EY Tech

ProjectPro is an awesome platform that helps me learn much hands-on industrial experience with a step-by-step walkthrough of projects. There are two primary paths to learn: Data Science and Big Data. In each learning path, there are many customized projects with all the details from the beginner to the expert. As a new data science learner, you can just follow these projects to master the important techniques quickly. It is really helpful for both my research and job searching. Hope you can come and join ProjectPro to win a great future for yourself.

Jingwei Li

Graduate Research assistance at Stony Brook University

ProjectPro is a unique platform and helps many people in the industry to solve real-life problems with a step-by-step walkthrough of projects. A platform with some fantastic resources to gain hands-on experience and prepare for job interviews. I would highly recommend this platform to anyone looking to upskill and stay updated with the latest projects and solutions. Overall this platform is awesome and worth the money spent as we get a lot of value out of it and helps soar our career to greater heights.

Anand Kumpatla

Sr Data Scientist @ Doubleslash Software Solutions Pvt Ltd