Want to make sense of the volumes of data you have collected? Need to incorporate data-driven decisions into your process? This course provides an overview of machine learning techniques to explore, analyze, and leverage data. You will be introduced to tools and algorithms you can use to create machine learning models that learn from data, and to scale those models up to big data problems. At the end of the course, you will be able to: • Design an approach to leverage data using the steps in the machine learning process. • Apply machine learning techniques to explore and prepare data for modeling. • Identify the type of machine learning problem in order to apply the appropriate set of techniques. • Construct models that learn from data using widely available open source tools. • Analyze big data problems using scalable machine learning algorithms on Spark. Software Requirements: Cloudera VM, KNIME, Spark
NP
This course provides you starting point to start working in KNIME and helps you in explaining basic statistics concepts along with its application in KNIME and Spark
RD
I am so much pleased with this course. Very much convinced by the presentation, way of speech, and the script of the Instructor. I am so excited to learn more about Machine Learning.
RR
The Course was great giving a good overview of all Machine Learning Concepts. It is good starting point to understand Basics and Deep dive into Learning.
BK
This is starting course for Machine Learning. Very well explained and after finishing this course, one will get interest in continuing and exploring further in Machine Learning field.
DS
Hands n exercises and corresponding quizzes are great !Content could be more detailed, but may be I felt it so given my past exposure to ML. I enjoyed learning Knime and Spark.
LO
Very well explained course on Machine Learning. I am grateful for the highly insightful course like this. I will recommend this course for all data enthusiasts.
JG
Excellent course. It teaches the basics with a great method and with practical exercises, involving real data. The sctructure is clear and it covers a good amount of topics. Well done San Diego!
PR
Excellent course, I learned a lot about machine learning with big data, but most importantly I feel ready to take it into more complex level although I realized there is lots to learn.
JA
Great overview about the machine learning in general. There are still lots not covered specially the Neural Network algorithms. Learning Spark MLlib was great advantage of this course.
PT
The course was the best introduction I had for machine learning. Helped me a lot to understand different concepts from people who already know about the subject and I didn't have any idea.
SM
The precise definitions for many commonly used terms were very helpful. You do not find these details in many books or documents. Also, using KNIME was also interesting
LB
This is by far the most enjoyable course of the big data specialization, i loved the teaching approach and enjoyed all the hands on exercises. Great job!
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It's a very basic course. In my opinion, if you have done some research by yourself this won't provide you new knowledge about the topic. The assignments can be done by a 5 year old and they don't even make you put an effort into it. In my opinion, not worth the money.
the course is good but the software is outdated and not maintained. avoid
Excellent course, I learned a lot about machine learning with big data, but most importantly I feel ready to take it into more complex level although I realized there is lots to learn.
The content of the course is basic but not bad. The wrost thing is that we can't use the virtual machine and follow the activities. The Jupyter doesn't work and KNIME version used in the video is very old.
This is starting course for Machine Learning. Very well explained and after finishing this course, one will get interest in continuing and exploring further in Machine Learning field.
I have to say this course is so disappointing. Almost all the instructions in hands-on assignment about the installation of system are wrong, which means you have to waste lots of time finding the right methodology by yourself. In addition, the lectures are theoretical and unrelated to assignments. You can have a very, very basic understanding about the tools mentioned in this course and what's why I think the staff should redesign the stucture of this course.
Yet another high quality course in the Big Data Specialisation track, providing proper theoretical background in combination with hands on material, which are both -as always- very well prepared. I really like the well-balanced, concise approach. As with any course, this is a start allowing you to continue, depending on your personal and professional interests, with one or more of the topics touched over the past few weeks.
I really liked this course. The way they walk you through the process is very great. Even though i had done the same process due to working in the industry, i was lacking the terminology and the ability to articulate it, this course made it clear me among many other things. Good way to shed some light on what to expect on a daily basis on the job as a data scientist.
Thank you for the great work.
Amazing course. Very easy to understand because of the way the doctor teaches. Also the hands-on activities are very easy to follow and I liked that in most of the hands-on questions I needed to do a modification in knime or spark challenging me to apply what what already learned and analyse what was going on. Thank you very much, excellent course.
What a wonderful way of learning Big Data Concepts on a wonderful platform of Coursera. The instructor is really amazing. Before taking this course i was afraid of machine learning process, but when i successfully finished this course, there is a big smile on my face.
Thanks to Coursera for providing such an amazing modern skills.
Muy completo, da buenas bases para adentrarse al mundo del aprendizaje automático, hay que tener previos conocimientos de estadística para entender
Nice
The particular good point for this course is a very complete illustration of machine learning life cycle. And it is also very good to introduce the tool Knime and provides hands on material how to use it so one could further its learning path. Exercise is good, material is well documented. What a disappointment is that I want to learn how machine learning algorithm could parellelly running in spark, or how machine learning algorithm could benefits from distriubted system, in this aspect I am not reach my goal because the couse did not teach in detail. Maybe I shall choose other course in the coursera. Anyway, big big thanks to the teachers.
"Я очень доволен этим курсом. Материал был представлен ясно и понятно, даже для новичков в области анализа данных. Я получил полезные знания о различных методах машинного обучения и их применении в реальных сценариях. Что особенно ценно, так это практические задания и проекты, которые помогли мне закрепить свои знания и применить их на практике. Благодаря этому курсу я чувствую себя готовым к применению полученных навыков в своей работе. Очень рекомендую этот курс всем, кто интересуется областью анализа данных и машинного обучения."
AMOOOOOO ESTE CURSO, entre los mejores de Big Data de la universidad de San Diego, super claro y organizado, amo la tutora de estos videos. En los foros los compañeros son super colaborativos y adore el contenido del curso. Excelente y super recomendado. I LOOOOOVE THIS COURSE, among the best in Big Data of the University of San Diego, super clear and organizaded, I love the tutor of these videos. In the forums the colleagues are super collaborative and I love the content of the course. Excellent and super recommended.
The course helped me understand the concepts of the machine learning from the very rudimentary level. It also laid the foundation for understanding and dealing with the practical implementation of the machine learning algorithms and their implementation in big data which eventually elevated my understanding of applications dealing machine learning with Big Data.
Thanks to all the mentors and instructors for everything- the teaching materials, quizzes, assignments and hands-on; everything was awesome.
I loved this course as it explained many of the machine learning algorithms that I was already familiar with with much more clarity than from online videos that I've seen. The equations were also explained very intuitively and with very practical handson exercises. I really recommend this course for anyone who needs a refresher on machine learning or brand new into it as the instructors Mai and Ilkay were so wonderful.
This is the best course of this specialization. Dr. Nguyen describes and teaches the contents of machine learning with clarity and digested knowledge.
I would suggest to add more in-depth contents to each of the machine learning category, especially clustering, classification and association, at least as optional contents in case the number of weeks allocated for course are restricted.
My name is Jose Antonio. I am looking for a new Data Scientist career (https://www.linkedin.com/in/joseantonio11)
I did this specialization to get new knowledge about Machine Learning and better understand the technology and your practical applications.
The course was excellent and the classes well taught by teachers.
Congratulations to Coursera team and Instructors.
Regards.
Jose Antonio.
Even though I am not very familiar with math, this course gave me a great overview of machine learning algorithms, data preparation, and model evaluation. The hands-on activities are not hard and offer a guide on applying the theoretical methods taught along the course using python commands together with Spark package, as well as the KNIME software which is pretty easy to learn