Web Intelligence and Big Data

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7/10 stars
based on  58 reviews
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FREE

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  • TBA

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Coursera online courses
Coursera's online classes are designed to help students achieve mastery over course material. Some of the best professors in the world - like neurobiology professor and author Peggy Mason from the University of Chicago, and computer science professor and Folding@Home director Vijay Pande - will supplement your knowledge through video lectures. They will also provide challenging assessments, interactive exercises during each lesson, and the opportunity to use a mobile app to keep up with yo...
Coursera's online classes are designed to help students achieve mastery over course material. Some of the best professors in the world - like neurobiology professor and author Peggy Mason from the University of Chicago, and computer science professor and Folding@Home director Vijay Pande - will supplement your knowledge through video lectures. They will also provide challenging assessments, interactive exercises during each lesson, and the opportunity to use a mobile app to keep up with your coursework. Coursera also partners with the US State Department to create “learning hubs” around the world. Students can get internet access, take courses, and participate in weekly in-person study groups to make learning even more collaborative. Begin your journey into the mysteries of the human brain by taking courses in neuroscience. Learn how to navigate the data infrastructures that multinational corporations use when you discover the world of data analysis. Follow one of Coursera’s “Skill Tracks”. Or try any one of its more than 560 available courses to help you achieve your academic and professional goals.

Provider Subject Specialization
Humanities
Sciences & Technology
4724 reviews

Course Description

This course is about building 'web-intelligence' applications exploiting big data sources arising social media, mobile devices and sensors, using new big-data platforms based on the 'map-reduce' parallel programming paradigm. In the past, this course has been offered at the Indian Institute of Technology Delhi as well as the Indraprastha Institute of Information Technology Delhi.
Reviews 7/10 stars
58 Reviews for Web Intelligence and Big Data

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Ethan Berl profile image
Ethan Berl profile image
10/10 starsCompleted
  • 4 reviews
  • 4 completed
7 years ago
Wow. I am so impressed by this course. Of the 11 Coursera classes and 1 edX course which I actively participated in so far (most of which were in Machine Learning, Artificial Intelligence, NLP, etc.), I think this one might be my favorite. Unlike some of the other courses from Stanford or Berkeley which cover similar subjects (and are great as well), this course takes a much more practical/applied approach and examines the technologies used to actually perform these techniques as well as give a great overview of current methods. Nowhere else would I learn as much about state of the art techniques like HTM. Nowhere else would I get to play around with data on web scale using techniques like Map-Reduce. Nowhere else could I get as complete of a picture of the current methods for having computers simulate intelligence, make deductions, run logic based systems, use collaborative filtering, perform pattern recognition, etc. To get the sam... Wow. I am so impressed by this course. Of the 11 Coursera classes and 1 edX course which I actively participated in so far (most of which were in Machine Learning, Artificial Intelligence, NLP, etc.), I think this one might be my favorite. Unlike some of the other courses from Stanford or Berkeley which cover similar subjects (and are great as well), this course takes a much more practical/applied approach and examines the technologies used to actually perform these techniques as well as give a great overview of current methods. Nowhere else would I learn as much about state of the art techniques like HTM. Nowhere else would I get to play around with data on web scale using techniques like Map-Reduce. Nowhere else could I get as complete of a picture of the current methods for having computers simulate intelligence, make deductions, run logic based systems, use collaborative filtering, perform pattern recognition, etc. To get the same value as this course gave, at the least I would have to take courses on Information Retrieval, Natural Language Processing, Machine Learning, Artificial Intelligence and then do the hard work of tying the different subjects together. Obviously I think that this class was amazing. The quizzes were good tests of if you had understood the content of the lectures. The homeworks were a little sporadic and seemed slightly poorly planned but they were challenging and most importantly, they actually taught you something rather than merely testing if you could parrot back what the lectures had just taught you. I had a feeling of accomplishment when I finally got my tf-idf calculation running in map-reduce format or when I implemented a Bayesian-net to play doctor at diagnosing disease. In terms of practical applications, this course blows every other course out of the water.
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Arash Pourhabibi-Zarandi profile image
Arash Pourhabibi-Zarandi profile image
6/10 starsCompleted
  • 4 reviews
  • 4 completed
4 years, 11 months ago
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Hamideh Iraj profile image
Hamideh Iraj profile image
2/10 starsDropped
  • 70 reviews
  • 60 completed
5 years, 7 months ago
I dropped the course because it was too long and had no concentration. Also it was distracting rather than integrating. Also the quizzes were terribly bad and made no sense to me.
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Mario Gómez Martínez profile image
Mario Gómez Martínez profile image
6/10 starsCompleted
  • 3 reviews
  • 3 completed
5 years, 7 months ago
I started this course with high expectatives from the topics covered. I completed the course with the feeling of having learned something, but not in a pleasant way. Some topics were covered in some detail (term-frequency IR techniques and Map-Reduce algorithms), while some other were merely scratched, which is ok given the introductory nature of the course. However, although the teachers were probably right in the selection of the topics and the practical approach, they failed in the presentation. Yes, the main drawback of this course is probably the poor quality of the material.
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dukebody profile image
dukebody profile image
4/10 starsCompleted
  • 2 reviews
  • 2 completed
5 years, 9 months ago
TL;DR: bad structured, not in-deep course, ask you to solve assignments using tools not explained. I studied Artificial Intelligence and have background in ML/DM methods, as well as intermediate programming skills using Python. My general impression is that the contents of this course are not well structured, they don't really connect (even if the instructor insists in so) and all in all it looks like a bunch of slightly related material, poorly covered. The in-lecture questions are not well-crafted, often they just ask you about random stuff you might have learned somewhere else. The students are asked to do homework using tools not explained in the lectures, at all. For example, perform Bayesian Network inference using SQL, when SQL is not explained in the course... And the last assignment is a data-mining task of a huge file, using tools not explained at all (Orange, Octave...?) you just have to learn to use on your own.
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Roma Gluskin profile image
Roma Gluskin profile image
4/10 starsTaking Now
  • 2 reviews
  • 1 completed
6 years ago
I took some courses in AI and ML in my undergraduate studies, and was curious about their large scale implementations. This course looked very promising for me. Unfortunately the instructors' English is very poor, the presentation format is very disorganised, and on top of that the questions are intentionally worded to try to sneak one up on you. I did find the programming assignments quite enjoyable to solve, even if the timed format was a little quirky (we had to precompute all the database, and 2 minutes to submit the answer to a query presented to us). At the end of the course the instructor had the audacity to peddle a book he just published on the course subject, which looked badly unethical (as if he explained badly on purpose, causing students to buy the book in hopes to get a better understanding and grade). I seriously considered dropping on multiple occasions, because I have better things to do with my time (and you can le... I took some courses in AI and ML in my undergraduate studies, and was curious about their large scale implementations. This course looked very promising for me. Unfortunately the instructors' English is very poor, the presentation format is very disorganised, and on top of that the questions are intentionally worded to try to sneak one up on you. I did find the programming assignments quite enjoyable to solve, even if the timed format was a little quirky (we had to precompute all the database, and 2 minutes to submit the answer to a query presented to us). At the end of the course the instructor had the audacity to peddle a book he just published on the course subject, which looked badly unethical (as if he explained badly on purpose, causing students to buy the book in hopes to get a better understanding and grade). I seriously considered dropping on multiple occasions, because I have better things to do with my time (and you can learn about map-reduce from Wikipedia), but I stuck with it(finishing soon). For me it's a good thing though that I took this course out of pure curiosity - I feel sorry for the kids in Indian Institute of Technology Delhi that took it and need to get a good grade.
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Saurav profile image
Saurav profile image
10/10 starsCompleted
  • 1 review
  • 1 completed
5 years, 11 months ago
A very well rounded course covering a wide range of topics. I did not have insight into big data before this course. Now I do have the basic foundation to build on. Overall, the lectures were great and assignments were relevant and helped in enhancing the understanding. I would recommend this course for big data and web intelligence.
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Marjan Ček profile image
Marjan Ček profile image
7/10 starsCompleted
  • 20 reviews
  • 17 completed
5 years, 11 months ago
The course covers a whole lot of information, so it doesn't go deep into any of them. It is nevertheless a very nice introduction to Big Data, and some of the programming assignments are very interesting, and none is particularly hard. The lectures are best viewed at 1.25x, but you quickly get used to it. I recommend it as a wide introduction to Big Data.
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Student profile image

Student

3/10 starsCompleted
5 years, 11 months ago
Pros Good course content. Cons Structure of course is not well adapted to web learning environment. Not quite able to go into details of each topics due to broad scope. Bad quality of course design compared with other MOOC courses.
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Student profile image

Student

5/10 starsCompleted
5 years, 11 months ago
The course covered a lot of relevant material very quickly and not thoroughly. The homework assignments demanded a level of depth of understanding that could only be gained by expending far more than the advertised 2-3hrs/week workload. Being skilled with Python, SQL, Orange, and discrete probability would also help reduce the workload but that was not my case, so I struggled with most of the assignments. Thankfully, student participation in the forums was excellent and we helped each other pull through. Attention to detail in the math slides in the lectures was also lacking - wrong symbols, confusing fonts, poor explanations ("I'll leave it to you to convince yourself this is correct."). On the plus side, it was very cool to run map-reduce on my laptop, run prediction models on human genome with Orange, etc. The course material is highly relevant for today's computer scientists.
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Student profile image

Student

9/10 starsCompleted
6 years ago
This course have taken lot of practicality in to account, which is very appreciable. I liked the course content ( very broad in nature rather than depth, which can be explored for further implementations ), which helps you to put together all the pieces of technology. One thing i found missing - reference material / books for the topics discussed could have been provided for better understanding / further depth of knowledge. Course outline, assignments and homework assignments felt very interesting and exciting for me, and were pretty helpful for me for a better practice.
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Student profile image

Student

7/10 starsCompleted
6 years ago
The course was useful although some of the areas were treated more theoretically that I would desire as I wanted to learn what existed for solving such problems because I am currently working full time. A version of this course for people who are working would be good. The one main comment was that the guest lectures were not helpful at all as the quality of the audio from students asking questions and spoken English of the guest lecturers was too poor to get anything from the presentation.
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Dharmesh Kishore profile image
Dharmesh Kishore profile image
10/10 starsCompleted
  • 1 review
  • 1 completed
6 years ago
I really found the course well structured.Examples considered gave good insight into the topic. The problems posed in the Homework Assignments challenged me to experiment and learn. Great part of the course was the introduction to other research problems of this field, and the guest lectures which covered such stuff. I had no background in Big Data but have been doing some work on Quality metrics in my professional life. This course helped me create a logical connection between the various real world problems and the academic work that goes into Big Data analytics. Mind this, this course is also about 'Web Intelligence'.
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Tiago Gomes profile image
Tiago Gomes profile image
8/10 starsCompleted
  • 1 review
  • 1 completed
6 years ago
Offers a global picture of big data and AI Good to create context to other deeper courses like Machine Learning
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Student profile image
Student profile image

Student

9/10 starsTaking Now
6 years ago
Nice course course overall. Would have been great to simplify/divide slides on some lectures Thanks for the great work done by Dr. Gautam Shroff
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Nitesh nahta profile image
Nitesh nahta profile image
9/10 starsTaking Now
  • 1 review
  • 0 completed
6 years ago
My prior experience to this subject was limited but this course gave me overall idea and framework to a direction that I can follow now overall pretty satisfied
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Jeff Winchell profile image
Jeff Winchell profile image
6/10 starsCompleted
  • 91 reviews
  • 66 completed
4 years, 9 months ago
I had to drop this course over half-way into it due to unplanned time constraints. I was definitely interested in the topic and it was my first class from a non-US university or non-elite university so I wondered what that would be like. I think the later (non-elite) was why I too often found myself sharply disagreeing with the professor's views. I've been in business intelligence for well over a decade and in databases for two decades and try to learn from the best. This professor was definitely not in that category. Still, it was a new area for me, so I persevered until my time constraints were too much. I would take it again if it was offered (to complete the material) and I'd try to ignore the wrong things the professor said. For those with far less experience I am afraid you may be taught wrong things, so be skeptical when something doesn't sound right and watch the forums for discussions on those topics.
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colin mcdermott profile image
colin mcdermott profile image
9/10 starsCompleted
  • 2 reviews
  • 2 completed
6 years, 2 months ago
Good structure, very insightful. Ideally I would have liked more time in fewer areas then the broad depth of this course. Still well worth doing and fun.
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Student

10/10 starsCompleted
6 years, 4 months ago
Dr. Shroff ties together a number of fragmented but highly related areas such as search, information theory, machine learning and big data in a single cohesive course. My favorite part of the course is the lectures on "Load" which demystify big data with unparalleled depth. The course is, at once, broad and deep. But it is, in my opinion, a graduate level course. Very highly recommended.
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Gustavo Seitun profile image
Gustavo Seitun profile image
4/10 starsDropped
  • 2 reviews
  • 1 completed
6 years, 4 months ago
Pitifully I choose this course as my first Mooc experience. I've not previous experience in any kind of programing, and the word "introduction" in the course title wrongly encourage me to think of it like a soft departure trip. Don't even think of it if you are not a coder.
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Kachun To profile image
Kachun To profile image
8/10 starsCompleted
  • 1 review
  • 1 completed
6 years, 4 months ago
Very informative about the scientific foundations, techniques & methodologies and application of big data and web intelligence. Definitely to be recommended for people who want to understand the basics of the subject. However, you need some maths and statistics foundation to understand the content. Only drawback is that one of the guest lecturer's accent was very difficult to understand.
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Daniel Gomes profile image
Daniel Gomes profile image
8/10 starsCompleted
  • 2 reviews
  • 2 completed
6 years, 5 months ago
The course covered a very range of topics (Hadoop, Databases, NoSQL, Naive and Bayes rule, Locality Sensitive Hashing, TF-IDF, MapReduce, Graph Database, Classification, Bayesian networks, etc). In my opinion some of them were very well explained and in detail but others not. One of the things I expected was more programing exercises to help understand the concepts. Besides that the homeworks and quizzes were good to put in practice the concepts we have learned. I recommend this course to everyone interested in Web Intelligence and Big Data. IMHO it worth every minute I spent on it.
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Duncan Murray profile image
Duncan Murray profile image
6/10 starsCompleted
  • 25 reviews
  • 24 completed
6 years, 5 months ago
Overall he does a good job of giving broad overview of a fairly diverse subject. Others have complained it was too shallow, and perhaps some parts were a bit glossed over, but to cover them all would make it a 50+ week MOOC. I have a good programming and SQL background, but still found the assignments to be difficult, seeing there was no test data or feedback which made it unclear. I would recommend this course if you wanted a good overview or the topics, but the assignments and exams offer no feedback, so if you are aiming for a certificate you would need to be prepared to work at it. PROS \- gives a taste of most of the topics \- speaks slowly in the starting lectures to allow people to get used to his accent (I had no trouble understanding, even on a smartphone) \- they provide the lecture slides in a single ZIP file to download. Very useful, but not as effective as some wiki pages CONS \- no useful wiki page. I take notes but fou... Overall he does a good job of giving broad overview of a fairly diverse subject. Others have complained it was too shallow, and perhaps some parts were a bit glossed over, but to cover them all would make it a 50+ week MOOC. I have a good programming and SQL background, but still found the assignments to be difficult, seeing there was no test data or feedback which made it unclear. I would recommend this course if you wanted a good overview or the topics, but the assignments and exams offer no feedback, so if you are aiming for a certificate you would need to be prepared to work at it. PROS \- gives a taste of most of the topics \- speaks slowly in the starting lectures to allow people to get used to his accent (I had no trouble understanding, even on a smartphone) \- they provide the lecture slides in a single ZIP file to download. Very useful, but not as effective as some wiki pages CONS \- no useful wiki page. I take notes but found it difficult to find where the information was for certain things - kept having to go through the videos \- the assignments need rethinking. They are kind of 'simple' once you *finish* them, but it is quite difficult to know if you are on the right track. You only get a couple of shots and entering a value in the answer but have no way of knowing if you are on the right track. A better approach would have been to give some test data which shows what is expected of that. \- I found the exam was difficult seeing it was so hard to find which video the information was buried. I would advise taking notes as you go. \- Just found out the grading will be on a sliding scale. This is a terrible idea, I would rather know how *I* did against the topic instead of being compared to a heap of other people I dont know.
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Student profile image

Student

8/10 starsCompleted
6 years, 5 months ago
Overall a good high-level overview course with practical skills-based assignments. If I had one criticism, it would be the discussion forum. It became a bit tedious to read through so many benign posts. (Almost a big data problem in itself.) It was probably due to the wide range of student experience. There were too many students complaining about not knowing how to do something. I expected more from students taking a graduate-level course. Overall, I would recommend the course.
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William Rosenfeld profile image
William Rosenfeld profile image
5/10 starsCompleted
  • 1 review
  • 1 completed
6 years, 5 months ago
The scope and depth of the class were outstanding and addressed a timely area of interest for IT professionals. Professor Shroff's presentations were well organized, simplified complex material, and interesting to follow. I learned a lot that makes me a better practitioner and improved my understanding of how the world of Amazon, Google, and NSA work. Several suggestions that would have made a good experience awesome: The lectures spent a lot of time using relatively complex mathematics to prove theoretical underpinnings of the techniques covered. I would have gotten much more from the lectures if they provided less formality and more worked examples, showing how to apply the techniques. Potential students should be prepared with strong math, particularly, probability, skills. Each of the homework problems was interesting and well conceived but lacking adequate direction. The discussion board back-filled in many cases but, for exampl... The scope and depth of the class were outstanding and addressed a timely area of interest for IT professionals. Professor Shroff's presentations were well organized, simplified complex material, and interesting to follow. I learned a lot that makes me a better practitioner and improved my understanding of how the world of Amazon, Google, and NSA work. Several suggestions that would have made a good experience awesome: The lectures spent a lot of time using relatively complex mathematics to prove theoretical underpinnings of the techniques covered. I would have gotten much more from the lectures if they provided less formality and more worked examples, showing how to apply the techniques. Potential students should be prepared with strong math, particularly, probability, skills. Each of the homework problems was interesting and well conceived but lacking adequate direction. The discussion board back-filled in many cases but, for example, I didn't benefit from the several hours I spent learning that Mincemeat needs to be patched to deal with UTF-8. A simple note to that effect would not have reduced my learning of map- reduce but would have eliminated substantial frustration. The Distributed File System and NoSQL database sections were of prime interest to me but were given relatively little attention. Expanding coverage of these key technologies and including a homework problem would be be great (assuming that lightweight tools are available). The two guest lectures wasted 20% of the lecture time for me. The topics were obtuse / theoretical, the speakers hard to understand, and their practice of addressing questions from the live audience, which we couldn't hear, was maddening. A process to allow discussion of homework by those that have completed it would be helpful in fully leveraging the learning. I spent substantial time beyond the minimum on the homeworks and would like to have discussed my questions and results. A forum section that could only be entered after completing the homework would address this need.
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Leonardo Zambaldi profile image
Leonardo Zambaldi profile image
10/10 starsCompleted
  • 1 review
  • 1 completed
6 years, 5 months ago
Nice course at all. Really liked the stucture and well planned classes. Easy to follow , provided me a great variety of topics Nice lectures and great job Dr. Gautam Shroff.
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Vio Belc profile image
Vio Belc profile image
9/10 starsCompleted
  • 1 review
  • 1 completed
6 years, 5 months ago
I am an IT professional and my desire was to expand my set of skills. That being said, the course on big data and web intelligence provided me with exactly what I was expecting: it introduced me to the paradigm of big data in a pleasant way, at my own pace and it allowed me to try hands-on the methods currently used in the above-mentioned paradigm. Thank you very much prof. Shroff for putting this together and making it easy to follow for whoever is interested.
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Student

6/10 starsCompleted
6 years, 5 months ago
A good course talking about diverse topics, and that might be a mistake as well. It is a good overview course topic-wise, yet the materials and slides used are not well done and they are ugly and unexplicative. I don't doubt the knowledge of the instructor but for sure should improve the slides. Also, the last homework seemed to me pretty bad designed.
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Student

3/10 starsCompleted
6 years, 5 months ago
Too dry and academic, lack of focus, confusingly worded homework assignments, and a FINAL EXAM! This was clearly just a university course put online and not something planned with an MOOC audience in mind.
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Nikhil sarpotdar profile image
Nikhil sarpotdar profile image
6/10 starsCompleted
  • 4 reviews
  • 4 completed
6 years, 5 months ago
This is a great course. I have the following suggestions for your course: 1) Slides have too much text. Please add more graphics, animation, movement etc on the slides. Even if you actually take a pen and write stuff (underlining, drawing rough figures) helps break the monotonicity of the slides. It helps me concentrate and draws my attention to the part of the slide or concept you are talking about. Online courses can be made more "interactive" if it isn't just a slide accompanied with a voice. 2) I think the course organization can be changed to better tie up the concepts more tightly. Most of the time I was going through weekly lectures as stand alone units and it was only when attempting the hw questions that I had to think and tie the concepts together. 3) Finally this course needs SQL background. You should add a lecture giving some background about SQL in the first week. 4) Any reason why you used octo.py and mincemeat.py ? Th... This is a great course. I have the following suggestions for your course: 1) Slides have too much text. Please add more graphics, animation, movement etc on the slides. Even if you actually take a pen and write stuff (underlining, drawing rough figures) helps break the monotonicity of the slides. It helps me concentrate and draws my attention to the part of the slide or concept you are talking about. Online courses can be made more "interactive" if it isn't just a slide accompanied with a voice. 2) I think the course organization can be changed to better tie up the concepts more tightly. Most of the time I was going through weekly lectures as stand alone units and it was only when attempting the hw questions that I had to think and tie the concepts together. 3) Finally this course needs SQL background. You should add a lecture giving some background about SQL in the first week. 4) Any reason why you used octo.py and mincemeat.py ? There seems to be a mapreduce.py package that is very intuitive and easy to use. Finally please add some more programming assignments that work on real life projects, data analytics, web analytics, big data. The course currently seems too theoretical. Thanks for your hard work. Please take these suggestions as positive feedback. Appreciate you taking time to teach this course.
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