Today we shall be talking in detail about an online course titled “Taming Big Data with MapReduce and Hadoop”. We believe proficiency in “Big Data” analysis clearly stands out in the realm of valuable skills. This course is designed to help you familiarize yourself with two pivotal technologies. One is MapReduce and the other one is Hadoop. Did you ever think about how colossal amounts of data, like the entirety of the internet are managed continuously and efficiently say by Google?
| Taming Big Data with MapReduce and Hadoop | |||
| Sundog Education | |||
| TTC Rating | 4.3 | ||
| Total Reviews Analyzed | 587 | ||
| Duration | 5 Hours | ||
| Enrollments | 24,000+ | ||
| Skill Level | Introductory | ||
| Course Type | Self-paced | ||
| Accreditation | – | ||
Disclaimer! Our comparison is based on authentic learner feedback and aims to provide valuable insights to the learning community. We maintain fairness, objectivity, and accuracy in our assessments. | |||
With the help of this course, you will understand all those techniques allowing you to employ them on your own Windows system. This course is an opportunity to grasp the art of framing data analysis problems as MapReduce challenges. The course features over 10 practical examples for an enhanced learning experience. With that, you will learn to scale all these solutions or operate seamlessly on cloud computing services making the course a comprehensive journey into the world of big data.
Key Strength:Clear and comprehensive instructionThe course was given much appreciation for its instructor’s adeptness in simplifying intricate MapReduce and Hadoop concepts. Learners claimed that the course offers detailed yet understandable explanations that demystified complex topics efficiently. Interactive hands-on learningAll the practical exercises were highly valued by the students and they appreciated the applicability to real-world scenarios. The following approach led to a deeper understanding of the material, despite a few concerns about the pace and depth of code explanation. Expertise and engaging teaching styleFrank Kane’s expertise along with his engaging teaching style resonates positively and keeps the learners interested. However, there were some concerns about fast pacing, and also learners felt the need for more detailed code explanations impacting the learning experience. Structured learning materialsThe structure and material of the course were appreciated for their organization and user-friendly nature. Whereas the majority of the praise was given to the well-organized lectures. Some learners also raised their concerns about repetitive examples. Relevance to practical applicationA lot of students appreciated the course’s real-world applicability which emphasized how the content enriched their understanding and ability to apply MapReduce in professional settings. Accessibility and instructor supportThe course’s accessibility and instructor responsiveness were also applauded by the students. The course was especially feasible for beginners. Nonetheless, there were some learners who highlighted challenges with certain concepts and sought more comprehensive explanations. Preparation for real-world useThis course was deemed as a solid ground for implementing MapReduce practically by learners instilling confidence in their abilities. Key Challenges:Outdated materialThere were a lot of complaints by users regarding the course featuring outdated content including Python 2.7 usage. Some material was dated back to 2015 leaving the course feeling irrelevant to current industry standards. Technical challenges with toolsThere were multiple reviews expressing frustration over technical obstacles. Some claimed there were a lot of issues during setup and with tools like Enthought Canopy and MRJob that hindered the learning experience. |
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