Data analysis using R - Course overview - Lecture 1 (Part 1)

Introduction to the course, what you will learn during the course, and introduction into the history and future of computation and programming.

This is a live-stream recording of the 50+ hour MSc and PhD lecture series: "Data analysis using the R language for statistical computing", given digitally during the Covid19 pandemic at the Humboldt University in Berlin organized and lectured by Dr Danny Arends.

Chapters:
00:00 Welcome and Course Overview
16:48 What you will be able to do after the course
19:52 Introduction into R
23:04 History of computation
44:25 Quantum computers - Present and Future
47:55 D-Wave One (128 qubits)
49:09 D-Wave Advantage
52:42 History of programming languages
58:57 Why learn R ?

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[imomjonkhamid]

many thanks. its very clear and comprehensive. Its great that you make it open and available for everyone

[yvesdusabirema]

I have little experience in programming and statistics, but I am interested in this course in order to go deep. thx

[tagrid]

Thank you very much. I love the way you explain things. PERFECT!

[czfovyx]

It's very beautifully and usefully, sir! Thank you!

[hectormathonsi]

Hi Professor,

First of all, I want to thank you for this course. It's really challenging to find R programming courses that focus on statistical analysis, so I truly appreciate it.

I'm currently majoring in statistics and computer science and looking to advance my knowledge in both statistics and analysis. While working on the 2021 version of the course (I'm still on the first lecture), I discovered the 2022 version. I wanted to ask if the 2022 version is an upgrade of the 2021 course. Should I switch to the 2022 version, or continue with the 2021 one?

[Calmasastone]

Good day, Danny.

I'm glad I came across your channel. I've been self-educating myself in the field of analytics (theory, sql, python, power bi, excel) since Jul 2022 using different ways and I'm certain this course will be a great addition, since I've already got used to basics in Python and find R is more attractive as a future data analyst.

Your comprehensive approach by teaching others is really awesome! You taught people not only R functions itself, but you'd also covered the history, which I trully appreciate!
My speaking/writing English aren't that good as reading/listening, because I seriously started learning English only in 2021 but I'm working on it.

I was wondering if you could share your point of view about one question: do you think we can use R visualization in most cases or we'd retain Power BI instead to provide our reports to the stakeholders / team members? Cause I'm trying to figure out which one should I focus on as a future data analyst (but for me R seems more suitable and flexable rather than Power BI).

Best wishes,
Anton.

[avtejsingh]

Many thanks for this
It says we will have n=13/14 lectures, but the playlist has 34 lectures. Is the playlist correct, Danny?

[bethells]

Good god, an hour before we start talking R :) 🙂

[oacho]

Hi Danny, I am curious to hear your professional opinion about how to fit a model that I find to be challenging. I have measurements of oxygen consumption taken at 4 different temperatures for 520 eggs belonging to 80 species of insects. The goal of my model is to look at how a series of predictors like location, mortality ecc. influence the slopes of the lines that describe the change in oxygen consumption across the 4 measurement temperatures. Oxygen consumption intuitively increases with egg mass, measurement temperature and age of the egg. What I do not understand is how to make these slopes the dependent variables. If I first make a model like oxygen~egg mass+age+measurement temperature and then I use the slopes for each species as dependent variable in a model like slopes~site+mortality+ambient temperature is that correct? Or is that discourage because I am doing statistics on statistics? Conversely, if I build only one model like oxygen~egg mass+age+measurement temperature is this model actually looking at slopes? Sorry for the long question but I find it hard to get a reasonable answer by myself.
Cheers

[chrischen]

Wish you could use a different mic. It's hard to hear with the speaker.

[KatumbaJoseph-fshw]

great to be here, may i be guided on how to reach out to you

[thaborolffy]

Would be nice to start this course with someone else.looking for accountability partner