Learn Big Data Hadoop Free Course with Certificate

Make future-ready data-driven solutions with our Big Data Hadoop Certification free of cost!

  • Explore the benefits of Hadoop and its ecosystem for storing, processing, and analyzing Data
  • Learn to manage and analyze massive Datasets with ease and efficiency
  • Gain expertise in processing vast Datasets and making Data-driven decisions at scale
  • 450,000 + Professionals trained
  • 250 + Workshops every month
  • 100 + Countries and counting

Dive into the world of Big Data processing using Hadoop

Explore the world of Big Data using Hadoop with our free online course, designed for beginners. In this comprehensive 13+ hour self-paced learning journey, you'll delve into the transformational power of Big Data processing using Hadoop.

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  • 13+ Hours of Self Learning Content 

  • Unlock Knowledge with Interactive Videos and eBooks 

  • Elevate Your Learning Experience with Flash Cards 

  • Accelerate Progress with Auto-Graded Assessments 

  • Test Your Learning with Recall Quizzes 

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Data Analysts

Data Engineers

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Software Developers

Business Intelligence Professionals

IT Managers

The KnowledgeHut Edge

Superior Outcomes

Focus on skilled-based outcomes with advanced insights from our state-of-the art learning platform. 

Immersive Learning

Go beyond just videos and learn with recall quizzes, interactive ebooks, case studies and more. 

World-Class Instructors

Course instructors and designers from top businesses including Google, Amazon, Twitter and IBM. 

Real-World Learning

Get an intimate, insider look at companies in the field through real-world case studies. 

Industry-Vetted Curriculum

Curriculum primed for industry relevance and developed with guidance from industry advisory boards. 

Continual Support

Learn better with support along the way. Get 24/7 help, stay unblocked and ramp up your skills. 


Learning Objective: Explore Big Data's significance, applications, and Hadoop basics. Grasp its management, architecture, and components like HDFS and MapReduce. Gain a solid foundation in Big Data and Hadoop's potential for data-driven industries.  

  • Introduction to Big Data and Hadoop
  • Introduction to Big Data
  • Big Data, Data Science and Its Use Cases
  • Introduction to Hadoop
  • Concepts of Hadoop
  • Features of Hadoop
  • Hadoop Architecture and Ecosystem 

Learning Objective: Discover HDFS architecture and commands, understand Hadoop's structure. Gain proficiency in Hadoop for effective large data management.  

  • Introduction to HDFS and YARN
  • HDFS Characteristics and Its Architecture
  • Concepts of HDFS
  • HDFS Command Line
  • Hadoop Architecture 

Learning Objective: Explore MapReduce and its role in handling vast data. Grasp its functioning and hands-on applications like TF-IDF and Word Count. Gain a foundational understanding of MapReduce's significance in Big Data management with Hadoop.  

  • Introduction to MapReduce
  • Introduction to MapReduce and its Advantages
  • How does MapReduce Work?
  • MapReduce Processing and TF-IDF
  • MapReduce Word Count Program
  • MapReduce Execution  

Learning Objective: Develop a strong grasp of Bash shell scripting, managing permissions, superuser rights, and advanced techniques like redirections and grouping. Explore Data transfer using Sqoop and Flume in Hadoop. Explore Apache Sqoop for RDBMS interactions and Apache Flume for data streaming. Acquire practical skills in Data transfer techniques, amplifying your capabilities in Big Data processing with Hadoop.  

  • Overview of Data Ingestion and Egestion into Hadoop
  • Introduction to Data Ingestion and Egestion Using Sqoop
  • Introduction to Apache Sqoop and Its Features
  • Architecture of Sqoop and Its Import and Export Process
  • How can You Use Sqoop to Get Data from RDBMS?
  • How to Send Data from Hadoop into RDBMS?
  • Introduction to Apache Flume and Its Features
  • Flume Architecture and Failure Handling
  • Flume Demonstration
  • Downloading and Streaming Data from Twitter Using Flume into HDFS
prerequisites for Big Data Hadoop Free Course


Basic knowledge of programming languages like Python, Scala, Java.

Understanding of SQL and RDBMS.

Frequently Asked Questions

Learning Big Data Hadoop

Big Data Hadoop is a robust and open-source distributed computing framework intended to manage massive volumes of information efficiently and cost-effectively. It permits organizations to process, store, and analyze extensive and diverse Datasets that surpass the capabilities of traditional Data processing systems. Hadoop's central components, such as Hadoop Distributed File System (HDFS) and MapReduce, enable information to be distributed across multiple nodes and processed in parallel, ensuring quicker and more scalable Data processing. With its capability to handle organized, semi-organized, and unorganized Data, Large Data Hadoop has become a crucial tool for contemporary Data-driven enterprises to obtain valuable insights and make informed decisions. 

Acquiring knowledge of Big Data Hadoop is essential for several reasons. Firstly, it equips individuals with the capability to manage and examine enormous Datasets efficiently, a skill of great importance as Data continues to expand exponentially. Secondly, Hadoop's dispersed computing abilities provide economical solutions to process and store massive-scale Data. Thirdly, proficiency in Hadoop unveils numerous career opportunities in Data analytics, Data engineering, and other Data-associated roles. Lastly, with Hadoop being an intrinsic part of the Vast Data ecosystem, acquiring knowledge empowers professionals to work with other related tools and technologies, making them valuable resources for Data-focused organizations seeking to derive valuable insights and make Data-driven decisions. 

To learn Big Data Hadoop, you can follow these steps: 

  • Start with online tutorials and courses: Platforms like KnowledgeHut provide comprehensive Hadoop courses suitable for beginners. 
  • Read books and documentation: Explore Hadoop-associated books and official Apache Hadoop documentation to gain extensive knowledge. 
  • Practice with hands-on projects: Establish a Hadoop cluster on your local drive or cloud platform and work on real-life projects to apply your learning. 
  • Join online communities: Engage in Hadoop forums and communities to interact with specialists and seek assistance when required. 
  • Attend workshops and webinars: Seek out workshops and webinars conducted by specialists to deepen your comprehension. 
  • Pursue certifications: Choose recognized Hadoop certifications to enhance your credibility and job prospects in the Big Data domain.

Beginners can get started with Hadoop by following these steps: 

  • Understand the basics: Understand Big Data, Hadoop's function, and its essential components such as HDFS and MapReduce. 
  • Set up a Hadoop environment: Install Hadoop on a virtual machine or employ cloud-based platforms like AWS or Azure. 
  • Take online courses: Enroll in beginner-friendly Hadoop courses. 
  • Practice with sample projects: Undertake small-scale projects to utilize your knowledge and become acquainted with Hadoop's features. 
  • Join Hadoop communities: Participate in forums and communities to seek guidance and learn from experienced Hadoop practitioners. 
  • Explore real-world Datasets: Utilize openly accessible Datasets to practice Data processing and analysis using Hadoop. 
  • Consider certifications: Pursue Hadoop certifications to authenticate your abilities and enhance your credibility in the job market. 

As Hadoop is created using Java, a strong foundation in Java programming is required to get started with Big Data Hadoop. It is crucial to be familiar with Linux environments, fundamental command-line operations, and networking ideas. It is also essential to understand the principles of distributed computing and the components of the Hadoop ecosystem, such as HDFS (Hadoop Distributed File System) and MapReduce. For efficiently processing and analyzing Big Datasets using Hadoop, proficiency in SQL, Databases, and programming in languages like Python can be helpful. 

The self-paced Big Data Hadoop course is free. The length of time it takes you to finish the course will therefore depend on how much time you spend on each module and the activities. Three months should be more than enough if you commit a few hours each day to the course and use some of that time to put what you have learned into practice.

You can broaden your skill set by putting the many ideas you learn in class to use and by utilizing additional course materials. As a result, learning will continue long after the course is done, even if you complete it in three months or less. KnowledgeHut provides specific courses and materials to assist you in mastering Big Data Hadoop if you wish to study online. 

The fundamentals of Big Data and Hadoop are covered in this free course provided by KnowledgeHut, along with an introduction to the architecture of Hadoop and its parts, such as HDFS and MapReduce. It discusses the methods used in the Hadoop ecosystem for Data intake, storage, and processing. The course digs into fundamental Hadoop programming, putting a focus on Java for MapReduce workloads. It introduces cluster management, fault tolerance, and Data scalability. The course may also cover related technologies like Hive, Pig, and HBase to give students a basic grasp of Big Data and Hadoop's function in managing enormous Datasets. 

Yes, having coding skills helps when using Hadoop for Big Data. While the Hadoop ecosystem provides tools like Hive and Pig that enable some tasks to be carried out without requiring a great deal of coding, more complex tasks like creating MapReduce jobs, processing customized Data, and optimizing performance require a strong grasp of languages like Java, Python, or Scala. Coding expertise improves the capacity to fully utilize Hadoop's features for effective Data processing and analysis. 

While mastering Big Data Hadoop's intricate ecosystem may seem challenging, breaking down components like HDFS, MapReduce, and YARN becomes achievable through dedicated learning and proper resources. Online tutorials, courses, and tools simplify the process. While mastery may take time, grasping its basics empowers professionals to adeptly manage and analyze extensive datasets. Kickstart your journey with KnowledgeHut's free Big Data using Hadoop course, the ideal starting point for gaining essential skills. 

Certification and Career Scope

Yes! You will receive a certificate of completion from KnowledgeHut once you have successfully completed the free Big Data Hadoop course. Numerous KnowledgeHut graduates use their course certificates to highlight their talents to networks and potential employers.

However, working on actual projects and adding them to your portfolio will provide you with the opportunity to demonstrate your newly acquired skills in addition to receiving the certificate. Industry leaders who contribute to our curriculum and use our tech programs to teach their own employees highly respect KnowledgeHut's courses. 

Once you complete the free online course for Big Data and Hadoop, you will be prepared to advance your knowledge. A specialization in allied disciplines like Data Analytics or Machine Learning, as well as advanced Hadoop topics like Hadoop administration, are also worthwhile options. Attending classes on Database management, Data visualization, and cloud platforms can also help you develop your knowledge. Your expertise can be strengthened by working on practical projects or by participating in Data science groups. Make sure your next steps are tailored to your professional objectives to ensure that you have a diverse skill set for the ever-changing field of Big Data technology. 

Yes, Big Data Hadoop skills are still in high demand. In order to gather insights and make wise decisions, organizations from a variety of industries understand the significance of processing and analyzing enormous datasets. Despite the emergence of newer technologies like Spark and cloud-based solutions, Hadoop continues to play a vital role in handling complicated Data processing jobs. Data engineers, Big Data Analysts, Data Scientists, and Hadoop developers are among the positions that employers are looking for in candidates that are knowledgeable in the Hadoop ecosystem, which includes HDFS and MapReduce. As the market landscape continues to change, it is crucial to stay current with related technology. 

Big data market size is anticipated to increase globally, from $138.9 billion in 2020 to $229.4 billion by 2025. It goes without saying that if the sector grows to such a large extent, so will the demand for expertise. 

The free Big Data using Hadoop course can be completed to gain access to a variety of job prospects. Work as a Hadoop Developer/Administrator, Data Engineer, or Big Data Analyst, for example. These positions entail planning, creating, and improving Hadoop-based data processing and analysis solutions. Consider roles in data warehousing, ETL (Extract, Transform, Load) procedures, or cloud-based data solutions as further career options.

In order to derive the most valuable insights from the data, many businesses have realized the value of Big Data management and are increasingly moving in that direction. Therefore, one needs to be familiar with Hadoop in order to meet the growing demand for Big Data management. 

Your foundation from the course can serve as a stepping-stone towards a satisfying career in domains linked to Data management, analysis, and technology as the demand for workers experienced in big data technologies rises. To tap into these opportunities, learn Big Data Hadoop for free and position yourself at the forefront of this evolving field. 

Yes, Big Data Hadoop holds significant potential for job opportunities. As businesses collect and process enormous amounts of data, there is a growing demand for experts in the Hadoop ecosystem. In demand across sectors are positions like data engineer, data analyst, and Hadoop developer. Knowledge of Hadoop can open doors to lucrative employment opportunities, professional advancement, and participation in cutting-edge data projects. But if you combine your Hadoop expertise with understanding of related technologies like Spark, cloud computing, and data visualization, you can improve your career prospects even more and make sure you're prepared for the rapidly changing data landscape. 

Big Data Hadoop developers' pay in India varies depending on their expertise, location, and company's size. Entry-level developers can expect to make between 4-6 lakhs a year on average. Salary levels with a few years of experience might range from 6 to 12 lakhs per year. Senior developers and specialists with deep knowledge may be paid more, anywhere from 12 to 20 lakhs or more. However, depending on the city, business, and market demand for Big Data, these numbers may change. 

Big Data Hadoop undoubtedly has a bright future. Although new technologies have arisen, such as cloud-based services and real-time processing, Hadoop's capacity for managing and analyzing huge datasets remains essential. It keeps getting better, integrating with tools like Spark and putting more of an emphasis on scalability and speed enhancements. Hadoop's role in storing, analyzing, and drawing conclusions from data remains vital as it grows rapidly. To be competitive, professionals should broaden their skill sets in relevant areas as the Big Data technology landscape is always changing. 

What Learners are Saying

Laura Williams Business Intelligence Professional

I had little experience in Big Data before taking this course, but now I feel confident in processing and analyzing large Datasets. It's definitely worth the time and effort! 

Mark Rodriguez IT Manager

The free Big Data Hadoop certification was an added bonus! The course addressed all of Hadoop's major elements, and the certification improved my resume. 

Emily Brown Software Developer

I wanted to improve my skills in Big Data processing as a software developer. My expectations were exceeded by the course. My hands-on experience was aided by the practical projects and analogies from real life. 

Michael Lee System Administrator

Even though I've taken a few online courses, this one was excellent. The videos were interesting, and the content was well-organized. I now have a solid foundation in Hadoop for my work thanks to the course. 

Sarah Johnson Data Analyst

As a Data analyst, this training has completely changed the way I work. Hadoop initially sounded overwhelming, but the lesson dissected it into understandable ideas. Highly recommended! 

John Smith Data Engineer

The Hadoop for Big Data Processing training was outstanding! The hands-on exercises were excellent for practical learning and the instructor's explanations were crystal clear. I am now comfortable managing large Databases.