Top 10 Big Data Courses to Learn in November 2024
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. Apache Spark with Scala – Hands On with Big Data!
Instructor: Sundog Education by Frank Kane
Apache Spark tutorial with 20+ hands-on examples of analyzing large data sets, on your desktop or on Hadoop with Scala!
Course Highlights:
- Rating: 4.57 ⭐ (17910 reviews)
- Students Enrolled: 98935
- Course Length: 32194 hours
- Number of Lectures: 73
- Number of Quizzes: 6
Apache Spark with Scala – Hands On with Big Data!, has an average rating of 4.57, with 73 lectures, 6 quizzes, based on 17910 reviews, and has 98935 subscribers.
You will learn about Develop distributed code using the Scala programming language Transform structured data using SparkSQL, DataSets, and DataFrames Frame big data analysis problems as Apache Spark scripts Optimize Spark jobs through partitioning, caching, and other techniques Build, deploy, and run Spark scripts on Hadoop clusters Process continual streams of data with Spark Streaming Traverse and analyze graph structures using GraphX Analyze massive data set with Machine Learning on Spark This course is ideal for individuals who are Software engineers who want to expand their skills into the world of big data processing on a cluster or If you have no previous programming or scripting experience, you'll want to take an introductory programming course first. It is particularly useful for Software engineers who want to expand their skills into the world of big data processing on a cluster or If you have no previous programming or scripting experience, you'll want to take an introductory programming course first.
Learn More About Apache Spark with Scala – Hands On with Big Data!
What You Will Learn
- Develop distributed code using the Scala programming language
- Transform structured data using SparkSQL, DataSets, and DataFrames
- Frame big data analysis problems as Apache Spark scripts
- Optimize Spark jobs through partitioning, caching, and other techniques
- Build, deploy, and run Spark scripts on Hadoop clusters
- Process continual streams of data with Spark Streaming
- Traverse and analyze graph structures using GraphX
- Analyze massive data set with Machine Learning on Spark
9. Python for Data Science and Machine Learning Bootcamp
Instructor: Jose Portilla
Learn how to use NumPy, Pandas, Seaborn , Matplotlib , Plotly , Scikit-Learn , Machine Learning, Tensorflow , and more!
Course Highlights:
- Rating: 4.59 ⭐ (146881 reviews)
- Students Enrolled: 737971
- Course Length: 89200 hours
- Number of Lectures: 184
- Number of Quizzes: 1
Python for Data Science and Machine Learning Bootcamp, has an average rating of 4.59, with 184 lectures, 1 quizzes, based on 146881 reviews, and has 737971 subscribers.
You will learn about Use Python for Data Science and Machine Learning Use Spark for Big Data Analysis Implement Machine Learning Algorithms Learn to use NumPy for Numerical Data Learn to use Pandas for Data Analysis Learn to use Matplotlib for Python Plotting Learn to use Seaborn for statistical plots Use Plotly for interactive dynamic visualizations Use SciKit-Learn for Machine Learning Tasks K-Means Clustering Logistic Regression Linear Regression Random Forest and Decision Trees Natural Language Processing and Spam Filters Neural Networks Support Vector Machines This course is ideal for individuals who are This course is meant for people with at least some programming experience It is particularly useful for This course is meant for people with at least some programming experience.
Learn More About Python for Data Science and Machine Learning Bootcamp
What You Will Learn
- Use Python for Data Science and Machine Learning
- Use Spark for Big Data Analysis
- Implement Machine Learning Algorithms
- Learn to use NumPy for Numerical Data
- Learn to use Pandas for Data Analysis
- Learn to use Matplotlib for Python Plotting
- Learn to use Seaborn for statistical plots
- Use Plotly for interactive dynamic visualizations
- Use SciKit-Learn for Machine Learning Tasks
- K-Means Clustering
- Logistic Regression
- Linear Regression
- Random Forest and Decision Trees
- Natural Language Processing and Spam Filters
- Neural Networks
- Support Vector Machines
8. AWS Certified Data Engineer Associate 2024 – 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: 4.58 ⭐ (5683 reviews)
- Students Enrolled: 52902
- Course Length: 77184 hours
- Number of Lectures: 288
- Number of Quizzes: 19
AWS Certified Data Engineer Associate 2024 – Hands On!, has an average rating of 4.58, with 288 lectures, 19 quizzes, based on 5683 reviews, and has 52902 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 2024 – 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
7. The definitive intro to big data science
Instructor: Erik Tromp
Learn the ins & outs of big data and data science in the most complete helicopter-view course that there is.
Course Highlights:
- Rating: 4.7 ⭐ (43 reviews)
- Students Enrolled: 317
- Course Length: 26257 hours
- Number of Lectures: 57
- Number of Quizzes: 0
The definitive intro to big data science, has an average rating of 4.7, with 57 lectures, based on 43 reviews, and has 317 subscribers.
You will learn about No-nonsense approach to big data science that anyone can understand regardless of prerequisite knowledge Get a broad overview of big data and data science Evolve from a career in BI to a career in big data Identify which topics you want to learn more about for your advancements Be able to make well-motivated decisions in your day-to-day job around data This course is ideal for individuals who are Best suitable for professionals of all layers of an organization that want to get a broad overview of big data science or If you are experience in big data AND data science or are looking for in-depth tutorials on specific tools, this course is NOT for you It is particularly useful for Best suitable for professionals of all layers of an organization that want to get a broad overview of big data science or If you are experience in big data AND data science or are looking for in-depth tutorials on specific tools, this course is NOT for you.
Learn More About The definitive intro to big data science
What You Will Learn
- No-nonsense approach to big data science that anyone can understand regardless of prerequisite knowledge
- Get a broad overview of big data and data science
- Evolve from a career in BI to a career in big data
- Identify which topics you want to learn more about for your advancements
- Be able to make well-motivated decisions in your day-to-day job around data
6. 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: 4.7 ⭐ (331803 reviews)
- Students Enrolled: 1418257
- Course Length: 187169 hours
- Number of Lectures: 654
- Number of Quizzes: 43
100 Days of Code: The Complete Python Pro Bootcamp, has an average rating of 4.7, with 654 lectures, 43 quizzes, based on 331803 reviews, and has 1418257 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
5. 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: 4.53 ⭐ (24739 reviews)
- Students Enrolled: 138641
- 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 4.53, with 67 lectures, based on 24739 reviews, and has 138641 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!
4. 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: 4.65 ⭐ (284 reviews)
- Students Enrolled: 3592
- Course Length: 36699 hours
- Number of Lectures: 97
- Number of Quizzes: 18
Data Lake Mastery: The Key to Big Data & Data Engineering, has an average rating of 4.65, with 97 lectures, 18 quizzes, based on 284 reviews, and has 3592 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
3. The Data Science Course: Complete Data Science Bootcamp 2024
Instructor: 365 Careers
Complete Data Science Training: Math, Statistics, Python, Advanced Statistics in Python, Machine and Deep Learning
Course Highlights:
- Rating: 4.58 ⭐ (146314 reviews)
- Students Enrolled: 719868
- Course Length: 111932 hours
- Number of Lectures: 550
- Number of Quizzes: 281
The Data Science Course: Complete Data Science Bootcamp 2024, has an average rating of 4.58, with 550 lectures, 281 quizzes, based on 146314 reviews, and has 719868 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 2024
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
2. 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: 4.57 ⭐ (1770 reviews)
- Students Enrolled: 15037
- 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 4.57, with 159 lectures, based on 1770 reviews, and has 15037 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
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: 4.53 ⭐ (30403 reviews)
- Students Enrolled: 183923
- 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 4.53, with 110 lectures, based on 30403 reviews, and has 183923 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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