Best Big Data Courses to Learn in February 2025
Looking to enhance your skills? We’ve curated a list of the top-rated big data courses available this month. These courses are highly rated by students and offer comprehensive learning experiences.
10. PySpark – Apache Spark Programming in Python for beginners
Instructor: Prashant Kumar Pandey
Master Apache Spark Programming in Python (PySpark) Using Free Databricks Community for Beginners with Capstone Project
Course Highlights:
- Rating: 4.55 ⭐ (11690 reviews)
- Students Enrolled: 68055
- Course Length: 50925 hours
- Number of Lectures: 94
- Number of Quizzes: 9
PySpark – Apache Spark Programming in Python for beginners, has an average rating of 4.55, with 94 lectures, 9 quizzes, based on 11690 reviews, and has 68055 subscribers.
You will learn about Apache Spark Foundation and Spark Architecture Data Engineering and Data Processing in Spark Working with Data Sources and Sinks Working with Data Frames and Spark SQL Using PyCharm IDE for Spark Development and Debugging Unit Testing, Managing Application Logs and Cluster Deployment This course is ideal for individuals who are Software Engineers and Architects who are willing to design and develop a Bigdata Engineering Projects using Apache Spark or Programmers and developers who are aspiring to grow and learn Data Engineering using Apache Spark It is particularly useful for Software Engineers and Architects who are willing to design and develop a Bigdata Engineering Projects using Apache Spark or Programmers and developers who are aspiring to grow and learn Data Engineering using Apache Spark.
Learn More About PySpark – Apache Spark Programming in Python for beginners
What You Will Learn
- Apache Spark Foundation and Spark Architecture
- Data Engineering and Data Processing in Spark
- Working with Data Sources and Sinks
- Working with Data Frames and Spark SQL
- Using PyCharm IDE for Spark Development and Debugging
- Unit Testing, Managing Application Logs and Cluster Deployment
9. Data Management Masterclass – The Complete Course
Instructor: George Smarts
Practical Data Management Course. Learn the best practices and specifics for every Data Management subject area (CDMP)
Course Highlights:
- Rating: 4.55 ⭐ (4146 reviews)
- Students Enrolled: 25143
- Course Length: 58386 hours
- Number of Lectures: 235
- Number of Quizzes: 15
Data Management Masterclass – The Complete Course, has an average rating of 4.55, with 235 lectures, 15 quizzes, based on 4146 reviews, and has 25143 subscribers.
You will learn about What is Data Management from A to Z All the different Data Management subject areas Best Practices on Data Management from the Industry How to implement Data Management practices within your organization This course is ideal for individuals who are Data Professionals that want to gain complete understanding of Data Management or Managers that need to understand the principles of Data Management or Anyone that wants to have a complete understanding of Data Management It is particularly useful for Data Professionals that want to gain complete understanding of Data Management or Managers that need to understand the principles of Data Management or Anyone that wants to have a complete understanding of Data Management.
Learn More About Data Management Masterclass – The Complete Course
What You Will Learn
- What is Data Management from A to Z
- All the different Data Management subject areas
- Best Practices on Data Management from the Industry
- How to implement Data Management practices within your organization
8. Taming Big Data with Apache Spark and Python – Hands On!
Instructor: Sundog Education by Frank Kane
PySpark tutorial with 20+ hands-on examples of analyzing large data sets on your desktop or on Hadoop with Python!
Course Highlights:
- Rating: 4.53 ⭐ (16718 reviews)
- Students Enrolled: 105835
- Course Length: 25197 hours
- Number of Lectures: 69
- Number of Quizzes: 0
Taming Big Data with Apache Spark and Python – Hands On!, has an average rating of 4.53, with 69 lectures, based on 16718 reviews, and has 105835 subscribers.
You will learn about Use DataFrames and Structured Streaming in Spark 3 Use the MLLib machine learning library to answer common data mining questions Understand how Spark Streaming lets your process continuous streams of data in real time Frame big data analysis problems as Spark problems Use Amazon's Elastic MapReduce service to run your job on a cluster with Hadoop YARN Install and run Apache Spark on a desktop computer or on a cluster Use Spark's Resilient Distributed Datasets to process and analyze large data sets across many CPU's Implement iterative algorithms such as breadth-first-search using Spark Understand how Spark SQL lets you work with structured data Tune and troubleshoot large jobs running on a cluster Share information between nodes on a Spark cluster using broadcast variables and accumulators Understand how the GraphX library helps with network analysis problems This course is ideal for individuals who are People with some software development background who want to learn the hottest technology in big data analysis will want to check this out. This course focuses on Spark from a software development standpoint; we introduce some machine learning and data mining concepts along the way, but that's not the focus. If you want to learn how to use Spark to carve up huge datasets and extract meaning from them, then this course is for you. or If you've never written a computer program or a script before, this course isn't for you – yet. I suggest starting with a Python course first, if programming is new to you. or If your software development job involves, or will involve, processing large amounts of data, you need to know about Spark. or If you're training for a new career in data science or big data, Spark is an important part of it. It is particularly useful for People with some software development background who want to learn the hottest technology in big data analysis will want to check this out. This course focuses on Spark from a software development standpoint; we introduce some machine learning and data mining concepts along the way, but that's not the focus. If you want to learn how to use Spark to carve up huge datasets and extract meaning from them, then this course is for you. or If you've never written a computer program or a script before, this course isn't for you – yet. I suggest starting with a Python course first, if programming is new to you. or If your software development job involves, or will involve, processing large amounts of data, you need to know about Spark. or If you're training for a new career in data science or big data, Spark is an important part of it.
Learn More About Taming Big Data with Apache Spark and Python – Hands On!
What You Will Learn
- Use DataFrames and Structured Streaming in Spark 3
- Use the MLLib machine learning library to answer common data mining questions
- Understand how Spark Streaming lets your process continuous streams of data in real time
- Frame big data analysis problems as Spark problems
- Use Amazon's Elastic MapReduce service to run your job on a cluster with Hadoop YARN
- Install and run Apache Spark on a desktop computer or on a cluster
- Use Spark's Resilient Distributed Datasets to process and analyze large data sets across many CPU's
- Implement iterative algorithms such as breadth-first-search using Spark
- Understand how Spark SQL lets you work with structured data
- Tune and troubleshoot large jobs running on a cluster
- Share information between nodes on a Spark cluster using broadcast variables and accumulators
- Understand how the GraphX library helps with network analysis problems
7. Spark and Python for Big Data with PySpark
Instructor: Jose Portilla
Learn how to use Spark with Python, including Spark Streaming, Machine Learning, Spark 2.0 DataFrames and more!
Course Highlights:
- Rating: 4.54 ⭐ (25064 reviews)
- Students Enrolled: 140911
- Course Length: 38069 hours
- Number of Lectures: 67
- Number of Quizzes: 0
Spark and Python for Big Data with PySpark, has an average rating of 4.54, with 67 lectures, based on 25064 reviews, and has 140911 subscribers.
You will learn about Use Python and Spark together to analyze Big Data Learn how to use the new Spark 2.0 DataFrame Syntax Work on Consulting Projects that mimic real world situations! Classify Customer Churn with Logisitic Regression Use Spark with Random Forests for Classification Learn how to use Spark's Gradient Boosted Trees Use Spark's MLlib to create Powerful Machine Learning Models Learn about the DataBricks Platform! Get set up on Amazon Web Services EC2 for Big Data Analysis Learn how to use AWS Elastic MapReduce Service! Learn how to leverage the power of Linux with a Spark Environment! Create a Spam filter using Spark and Natural Language Processing! Use Spark Streaming to Analyze Tweets in Real Time! This course is ideal for individuals who are Someone who knows Python and would like to learn how to use it for Big Data or Someone who is very familiar with another programming language and needs to learn Spark It is particularly useful for Someone who knows Python and would like to learn how to use it for Big Data or Someone who is very familiar with another programming language and needs to learn Spark.
Learn More About Spark and Python for Big Data with PySpark
What You Will Learn
- Use Python and Spark together to analyze Big Data
- Learn how to use the new Spark 2.0 DataFrame Syntax
- Work on Consulting Projects that mimic real world situations!
- Classify Customer Churn with Logisitic Regression
- Use Spark with Random Forests for Classification
- Learn how to use Spark's Gradient Boosted Trees
- Use Spark's MLlib to create Powerful Machine Learning Models
- Learn about the DataBricks Platform!
- Get set up on Amazon Web Services EC2 for Big Data Analysis
- Learn how to use AWS Elastic MapReduce Service!
- Learn how to leverage the power of Linux with a Spark Environment!
- Create a Spam filter using Spark and Natural Language Processing!
- Use Spark Streaming to Analyze Tweets in Real Time!
6. AWS Certified Data Engineer Associate 2025 – Hands On!
Instructor: Sundog Education by Frank Kane
AWS DEA-C01 certification prep course with exercises and a full-length practice exam. Redshift, Glue, Athena, and more
Course Highlights:
- Rating: 4.6 ⭐ (7006 reviews)
- Students Enrolled: 63501
- Course Length: 77548 hours
- Number of Lectures: 291
- Number of Quizzes: 19
AWS Certified Data Engineer Associate 2025 – Hands On!, has an average rating of 4.6, with 291 lectures, 19 quizzes, based on 7006 reviews, and has 63501 subscribers.
You will learn about Maximize your odds of passing the AWS Certified Data Engineer – Associate (DEA-C01) exam Design and implement data pipelines with AWS to ingest, store, and transform data Choose and design data stores, data models, data schemas, and data lifecycles. Maintain, operationalize, and orchestrate data pipelines with EventBridge, Airflow, AWS Step Functions,, and more Apply security, governance, and privacy best practices to your AWS data pipelines. Create data lakes with S3, Glue, Redshift and more Process batch and streaming data with Kinesis, EMR, containers, Lambda, and more This course is ideal for individuals who are Technologists seeking certification in data engineering technologies on Amazon Web Services It is particularly useful for Technologists seeking certification in data engineering technologies on Amazon Web Services.
Learn More About AWS Certified Data Engineer Associate 2025 – Hands On!
What You Will Learn
- Maximize your odds of passing the AWS Certified Data Engineer – Associate (DEA-C01) exam
- Design and implement data pipelines with AWS to ingest, store, and transform data
- Choose and design data stores, data models, data schemas, and data lifecycles.
- Maintain, operationalize, and orchestrate data pipelines with EventBridge, Airflow, AWS Step Functions,, and more
- Apply security, governance, and privacy best practices to your AWS data pipelines.
- Create data lakes with S3, Glue, Redshift and more
- Process batch and streaming data with Kinesis, EMR, containers, Lambda, and more
5. Data Lake Mastery: The Key to Big Data & Data Engineering
Instructor: Nikolai Schuler
Data Lake Mastery using AWS: A Shortcut to Success in Big Data, Cloud Data Engineering and Data Architecture
Course Highlights:
- Rating: 4.67 ⭐ (353 reviews)
- Students Enrolled: 4355
- Course Length: 36719 hours
- Number of Lectures: 97
- Number of Quizzes: 18
Data Lake Mastery: The Key to Big Data & Data Engineering, has an average rating of 4.67, with 97 lectures, 18 quizzes, based on 353 reviews, and has 4355 subscribers.
You will learn about Master the complete implementation of full-scale Data Lake solutions in the cloud Apply Data Lake concepts professionally in cloud data engineering Create a multi-layered security strategy for Data Lake protection Design & implement efficient data ingestion strategies in AWS Master Data Lake Architecture for effective cloud implementations Master Data Lake Governance & Security Master Leadership & Strategy Essentials for Successful Data Lakes Learn comprehensive access control strategies within Data Lakes Understand and implement robust monitoring and security in Data Lakes Enhance your career prospects with advanced Data Lake skills and knowledge This course is ideal for individuals who are Aspiring Data Engineers looking to start or advance their career or Cloud Technology Enthusiasts with an interest in Big Data or IT Professionals who want to expand their skillset to include Data Lake skills or Anyone that wants to add Data Lake skills to their skillset It is particularly useful for Aspiring Data Engineers looking to start or advance their career or Cloud Technology Enthusiasts with an interest in Big Data or IT Professionals who want to expand their skillset to include Data Lake skills or Anyone that wants to add Data Lake skills to their skillset.
Learn More About Data Lake Mastery: The Key to Big Data & Data Engineering
What You Will Learn
- Master the complete implementation of full-scale Data Lake solutions in the cloud
- Apply Data Lake concepts professionally in cloud data engineering
- Create a multi-layered security strategy for Data Lake protection
- Design & implement efficient data ingestion strategies in AWS
- Master Data Lake Architecture for effective cloud implementations
- Master Data Lake Governance & Security
- Master Leadership & Strategy Essentials for Successful Data Lakes
- Learn comprehensive access control strategies within Data Lakes
- Understand and implement robust monitoring and security in Data Lakes
- Enhance your career prospects with advanced Data Lake skills and knowledge
4. 100 Days of Code: The Complete Python Pro Bootcamp
Instructor: Dr. Angela Yu, Developer and Lead Instructor
Master Python by building 100 projects in 100 days. Learn data science, automation, build websites, games and apps!
Course Highlights:
- Rating: 4.71 ⭐ (349871 reviews)
- Students Enrolled: 1497306
- Course Length: 187172 hours
- Number of Lectures: 653
- Number of Quizzes: 43
100 Days of Code: The Complete Python Pro Bootcamp, has an average rating of 4.71, with 653 lectures, 43 quizzes, based on 349871 reviews, and has 1497306 subscribers.
You will learn about You will master the Python programming language by building 100 unique projects over 100 days. You will learn automation, game, app and web development, data science and machine learning all using Python. You will be able to program in Python professionally You will learn Selenium, Beautiful Soup, Request, Flask, Pandas, NumPy, Scikit Learn, Plotly, and Matplotlib. Create a portfolio of 100 Python projects to apply for developer jobs Be able to build fully fledged websites and web apps with Python Be able to use Python for data science and machine learning Build games like Blackjack, Pong and Snake using Python Build GUIs and Desktop applications with Python This course is ideal for individuals who are If you want to learn to code from scratch through building fun and useful projects, then take this course. or If you want to start your own startup by building your own websites and web apps. or If you are a complete beginner then this course will be everything you need to become a Python professional or If you are a seasoned programmer wanting to switch to Python then this is the quickest way. Learn through coding projects. or If you are an intermediate Python programmer then you know 100 days of code challenges will help you level up. It is particularly useful for If you want to learn to code from scratch through building fun and useful projects, then take this course. or If you want to start your own startup by building your own websites and web apps. or If you are a complete beginner then this course will be everything you need to become a Python professional or If you are a seasoned programmer wanting to switch to Python then this is the quickest way. Learn through coding projects. or If you are an intermediate Python programmer then you know 100 days of code challenges will help you level up.
Learn More About 100 Days of Code: The Complete Python Pro Bootcamp
What You Will Learn
- You will master the Python programming language by building 100 unique projects over 100 days.
- You will learn automation, game, app and web development, data science and machine learning all using Python.
- You will be able to program in Python professionally
- You will learn Selenium, Beautiful Soup, Request, Flask, Pandas, NumPy, Scikit Learn, Plotly, and Matplotlib.
- Create a portfolio of 100 Python projects to apply for developer jobs
- Be able to build fully fledged websites and web apps with Python
- Be able to use Python for data science and machine learning
- Build games like Blackjack, Pong and Snake using Python
- Build GUIs and Desktop applications with Python
3. Data Engineering Master Course: Spark/Hadoop/Kafka/MongoDB
Instructor: Navdeep Kaur
Full Hands on course to become Big Data Engineer: Spark/Kafka/Hadoop/Flume/Hive/Sqoop/MongoDB. Data Engineering course.
Course Highlights:
- Rating: 4.6 ⭐ (1848 reviews)
- Students Enrolled: 15937
- Course Length: 43036 hours
- Number of Lectures: 159
- Number of Quizzes: 0
Data Engineering Master Course: Spark/Hadoop/Kafka/MongoDB, has an average rating of 4.6, with 159 lectures, based on 1848 reviews, and has 15937 subscribers.
You will learn about Hadoop Ecosystem, Sqoop, Flume, Hive Expertise on writing code with Apache Spark Learn Kafka Fundamentals and using Kafka Connectors Learn writing queries and client in MongoDB Learn Data Engineering technologies This course is ideal for individuals who are Who want to learn Big data technologies or Who want to become Data Engineers It is particularly useful for Who want to learn Big data technologies or Who want to become Data Engineers.
Learn More About Data Engineering Master Course: Spark/Hadoop/Kafka/MongoDB
What You Will Learn
- Hadoop Ecosystem, Sqoop, Flume, Hive
- Expertise on writing code with Apache Spark
- Learn Kafka Fundamentals and using Kafka Connectors
- Learn writing queries and client in MongoDB
- Learn Data Engineering technologies
2. The Data Science Course: Complete Data Science Bootcamp 2025
Instructor: 365 Careers
Complete Data Science Training: Math, Statistics, Python, Advanced Statistics in Python, Machine and Deep Learning
Course Highlights:
- Rating: 4.59 ⭐ (149479 reviews)
- Students Enrolled: 739079
- Course Length: 112585 hours
- Number of Lectures: 553
- Number of Quizzes: 277
The Data Science Course: Complete Data Science Bootcamp 2025, has an average rating of 4.59, with 553 lectures, 277 quizzes, based on 149479 reviews, and has 739079 subscribers.
You will learn about The course provides the entire toolbox you need to become a data scientist Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow Impress interviewers by showing an understanding of the data science field Learn how to pre-process data Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!) Start coding in Python and learn how to use it for statistical analysis Perform linear and logistic regressions in Python Carry out cluster and factor analysis Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn Apply your skills to real-life business cases Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data Unfold the power of deep neural networks Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations This course is ideal for individuals who are You should take this course if you want to become a Data Scientist or if you want to learn about the field or This course is for you if you want a great career or The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills It is particularly useful for You should take this course if you want to become a Data Scientist or if you want to learn about the field or This course is for you if you want a great career or The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills.
Learn More About The Data Science Course: Complete Data Science Bootcamp 2025
What You Will Learn
- The course provides the entire toolbox you need to become a data scientist
- Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
- Impress interviewers by showing an understanding of the data science field
- Learn how to pre-process data
- Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
- Start coding in Python and learn how to use it for statistical analysis
- Perform linear and logistic regressions in Python
- Carry out cluster and factor analysis
- Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
- Apply your skills to real-life business cases
- Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
- Unfold the power of deep neural networks
- Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
- Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
1. The Ultimate Hands-On Hadoop: Tame your Big Data!
Instructor: Sundog Education by Frank Kane
Data Engineering and Hadoop tutorial with MapReduce, HDFS, Spark, Flink, Hive, HBase, MongoDB, Cassandra, Kafka + more!
Course Highlights:
- Rating: 4.62 ⭐ (30575 reviews)
- Students Enrolled: 185802
- Course Length: 52037 hours
- Number of Lectures: 110
- Number of Quizzes: 0
The Ultimate Hands-On Hadoop: Tame your Big Data!, has an average rating of 4.62, with 110 lectures, based on 30575 reviews, and has 185802 subscribers.
You will learn about Design distributed systems that manage "big data" using Hadoop and related data engineering technologies. Use HDFS and MapReduce for storing and analyzing data at scale. Use Pig and Spark to create scripts to process data on a Hadoop cluster in more complex ways. Analyze relational data using Hive and MySQL Analyze non-relational data using HBase, Cassandra, and MongoDB Query data interactively with Drill, Phoenix, and Presto Choose an appropriate data storage technology for your application Understand how Hadoop clusters are managed by YARN, Tez, Mesos, Zookeeper, Zeppelin, Hue, and Oozie. Publish data to your Hadoop cluster using Kafka, Sqoop, and Flume Consume streaming data using Spark Streaming, Flink, and Storm This course is ideal for individuals who are Software engineers and programmers who want to understand the larger Hadoop ecosystem, and use it to store, analyze, and vend "big data" at scale. or Project, program, or product managers who want to understand the lingo and high-level architecture of Hadoop. or Data analysts and database administrators who are curious about Hadoop and how it relates to their work. or System architects who need to understand the components available in the Hadoop ecosystem, and how they fit together. It is particularly useful for Software engineers and programmers who want to understand the larger Hadoop ecosystem, and use it to store, analyze, and vend "big data" at scale. or Project, program, or product managers who want to understand the lingo and high-level architecture of Hadoop. or Data analysts and database administrators who are curious about Hadoop and how it relates to their work. or System architects who need to understand the components available in the Hadoop ecosystem, and how they fit together.
Learn More About The Ultimate Hands-On Hadoop: Tame your Big Data!
What You Will Learn
- Design distributed systems that manage "big data" using Hadoop and related data engineering technologies.
- Use HDFS and MapReduce for storing and analyzing data at scale.
- Use Pig and Spark to create scripts to process data on a Hadoop cluster in more complex ways.
- Analyze relational data using Hive and MySQL
- Analyze non-relational data using HBase, Cassandra, and MongoDB
- Query data interactively with Drill, Phoenix, and Presto
- Choose an appropriate data storage technology for your application
- Understand how Hadoop clusters are managed by YARN, Tez, Mesos, Zookeeper, Zeppelin, Hue, and Oozie.
- Publish data to your Hadoop cluster using Kafka, Sqoop, and Flume
- Consume streaming data using Spark Streaming, Flink, and Storm
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