Complete Time Series Data Analysis Bootcamp In R (Udemy.com)

This is an excellent course for the utility and importance of various tools in R for time series data analysis. The course is ideally suited for my work and will significantly add to my knowledge base of the subject. The instructor has been simply brilliant in her lectures. Her knowledge of the subject is outstanding.

The course has immense potential for practical usage as it contains techniques for effective use of time series/ temporal data using statistical modelling and machine learning techniques in R. The instructor is well-versed with the subject and her teaching technique is interesting and easy to follow.

The course contains valuable information about use of statistical modelling and machine learning in R. It has immense possibilities for practical usage. The course is very useful and relevant for my work. The instructor's performance in explaining nuances of the concept is superb.

The course regarding use of statistical modelling and machine learning techniques in R while working time series and temporal data is an amazing course. I will be able to use the concepts for my work and the quality of my work will enhance significantly. The instructor's knowledge of the course is impressive.

The course contains valuable information for time series analysis using statistical modelling and machine learning techniques in R. The concept has high potential for practical applications. The instructor is knowledgeable about the subject and her delivery is lucid and effective.

the course contains valuable information and the lectures of the course have been well-arranged. The instructor has explained the concepts of the course in a clear and easy-to-understand manner. she has total command over finer nuances of the concepts.

Course objective stated its commitment to embracing the students' learning. While overall the course was good, I was highly disappointed with the response or lack thereof to many of the questions. Had only 2 questions answered out of the 7 submitted. High number of unanswered questions from other students plagued this course which does not speak well of embracing the students current or future pursuits. Thought that the lecturer could have provided better (more expanded) explanations on certain topics and/or codes: Fourier terms, ?XGBoost, BFAST and Github.

The course was very good. It reinforced my knowledge of R and provided me tips and knowledge regarding how to best approach a time series analysis problem. I also gained insights on using other approaches and frameworks such as machine learning and h2o. I will most likely go back and review a few sections in more detail to make sure I understand the code. Overall I found the material useful and applicable to the work I am currently doing. There were some minimal annoyances such as code files with ".txt" extensions in the course content. I needed to save them as ".R" files to take full advantage of "R" Studio features but, I consider that minor.

The course introduced me towards some additional methods for understanding & predicting time series data. However, the explanation provided in the lectures is pretty limited and rather focused on just the execution part. I was still able to understand the content (for most part) as I had some previous background on time series forecasting in R. For someone new, it would be kind of difficult to understand why we are doing certain steps.

Course is short and concise. Dr.Minerva explained common time-series techniques applicable in real-word. More in-depth explanation on few packages especially using neural-networks and deep-learning will help learner improve.