` box:
-
-
-
-reflection text
-
-
-
-
-## Dropdown summaries
-
-
You can hide additional information in a dropdown menu
-Here's more words that are hidden.
-
-
-## Print out session info
-
-You should print out session info when you have code for [reproducibility purposes](https://jhudatascience.org/Reproducibility_in_Cancer_Informatics/managing-package-versions.html).
-
-```{r}
-devtools::session_info()
-```
-
-[many links]: https://github.com/jhudsl/OTTR_Template
diff --git a/Course_Name.rds b/Course_Name.rds
new file mode 100644
index 00000000..ac98e3f6
Binary files /dev/null and b/Course_Name.rds differ
diff --git a/_bookdown.yml b/_bookdown.yml
index b163ca5a..040a22ba 100644
--- a/_bookdown.yml
+++ b/_bookdown.yml
@@ -1,9 +1,9 @@
-book_filename: "Course_Name"
+book_filename: "Season 1 Introduction to R"
chapter_name: "Chapter "
repo: https://github.com/jhudsl/OTTR_Template/
rmd_files: ["index.Rmd",
"01-intro.Rmd",
- "02-chapter_of_course.Rmd",
+ "lesson1.Rmd",
"About.Rmd",
"References.Rmd"]
new_session: yes
diff --git a/lesson1.Rmd b/lesson1.Rmd
new file mode 100644
index 00000000..a5e48d64
--- /dev/null
+++ b/lesson1.Rmd
@@ -0,0 +1,226 @@
+
+# A new chapter
+
+If you haven't yet read the getting started Wiki pages; [start there](https://www.ottrproject.org/getting_started.html).
+
+To see the rendered version of this chapter and the rest of the template, see here: https://jhudatascience.org/OTTR_Template/.
+
+Every chapter needs to start out with this chunk of code:
+
+
+```{r, include = FALSE}
+ottrpal::set_knitr_image_path()
+```
+# W1: Intro to Computing
+
+## Goals of the course
+
+- Fundamental concepts in high-level programming languages (R, Python, Julia, WDL, etc.) that is transferable: *How do programs run, and how do we solve problems using functions and data structures?*
+
+- Beginning of data science fundamentals: *How do you translate your scientific question to a data wrangling problem and answer it?*
+
+ {width="450"}
+
+- Find a nice balance between the two throughout the course: we will try to reproduce a figure from a scientific publication using new data.
+
+## What is a computer program?
+
+- A sequence of instructions to manipulate data for the computer to execute.
+
+- A series of translations: English \<-\> Programming Code for Interpreter \<-\> Machine Code for Central Processing Unit (CPU)
+
+We will focus on English \<-\> Programming Code for R Interpreter in this class.
+
+More importantly: **How we organize ideas \<-\> Instructing a computer to do something**.
+
+## A programming language has following elements: {#a-programming-language-has-following-elements}
+
+- Grammar structure (simple building blocks)
+
+- Means of combination to analyze and create content (examples around genomics provided, and your scientific creativity is strongly encouraged!)
+
+- Means of abstraction for modular and reusable content (data structures, functions)
+
+- Culture (emphasis on open-source, collaborative, reproducible code)
+
+Requires a lot of practice to be fluent!
+
+## What is R and why should I use it?
+
+It is a:
+
+- Dynamic programming interpreter
+
+- Highly used for data science, visualization, statistics, bioinformatics
+
+- Open-source and free; easy to create and distribute your content; quirky culture
+
+## R vs. Python as a first language
+
+In terms of our goals, recall:
+
+- Fundamental concepts in high-level programming languages
+
+- Beginning of data science fundamentals
+
+There are a lot of nuances and debates, but I argue that Python is a better learning environment for the former and R is better for the latter.
+
+Ultimately, either should be okay! Perhaps more importantly, *consider what your research group and collaborator are more comfortable with*.
+
+## Posit Cloud Setup
+
+Posit Cloud/RStudio is an Integrated Development Environment (IDE). Think about it as Microsoft Word to a plain text editor. It provides extra bells and whistles to using R that is easier for the user.
+
+Today, we will pay close attention to:
+
+- Script editor: where sequence of instructions are typed and saved as a text document as a R program. To run the program, the console will execute every single line of code in the document.
+
+- Console (interpreter): Instead of giving a entire program in a text file, you could interact with the R Console line by line. You give it one line of instruction, and the console executes that single line. It is what R looks like without RStudio.
+
+- Environment: Often, code will store information *in memory*, and it is shown in the environment. More on this later.
+
+## Using Quarto for your work
+
+Why should we use Quarto for data science work?
+
+- Encourages reproducible workflows
+
+- Code, output from code, and prose combined together
+
+- Extendability to Python, Julia, and more.
+
+More options and guides can be found in [Introduction to Quarto](https://quarto.org/docs/get-started/hello/rstudio.html) .
+
+## Grammar Structure 1: Evaluation of Expressions
+
+- **Expressions** are be built out of **operations** or **functions**.
+
+- Operations and functions combine **data types** to return another data type.
+
+- We can combine multiple expressions together to form more complex expressions: an expression can have other expressions nested inside it.
+
+For instance, consider the following expressions entered to the R Console:
+
+```{r}
+18 + 21
+max(18, 21)
+max(18 + 21, 65)
+18 + (21 + 65)
+length("ATCG")
+```
+
+Here, our input **data types** to the operation are **numeric** in lines 1-4 and our input data type to the function is **character** in line 5.
+
+Operations are just functions in hiding. We could have written:
+
+```{r}
+sum(18, 21)
+sum(18, sum(21, 65))
+```
+
+Remember the function machine from algebra class? We will use this schema to think about expressions.
+
+
+
+If an expression is made out of multiple, nested operations, what is the proper way of the R Console interpreting it? Being able to read nested operations and nested functions as a programmer is very important.
+
+```{r}
+3 * 4 + 2
+3 * (4 + 2)
+```
+
+Lastly, a note on the use of functions: a programmer should not need to know how the function is implemented in order to use it - this emphasizes [abstraction and modular thinking](#a-programming-language-has-following-elements), a foundation in any programming language.
+
+## Grammar Structure 2: Storing data types in the global environment
+
+To build up a computer program, we need to store our returned data type from our expression somewhere for downstream use. We can assign a variable to it as follows:
+
+```{r}
+x = 18 + 21
+```
+
+If you enter this in the Console, you will see that in the Environment, the variable `x` has a value of `39`.
+
+::: {.callout-tip}
+## Execution rule for variable assignment
+
+Evaluate the expression to the right of `=`.
+
+Bind variable to the left of `=` to the resulting value.
+
+The variable is stored in the environment.
+
+`<-` is okay too!
+:::
+
+The environment is where all the variables are stored, and can be used for an expression anytime once it is defined. Only one unique variable name can be defined.
+
+The variable is stored in the working memory of your computer, Random Access Memory (RAM). This is temporary memory storage on the computer that can be accessed quickly. Typically a personal computer has 8, 16, 32 Gigabytes of RAM. When we work with large datasets, if you assign a variable to a data type larger than the available RAM, it will not work. More on this later.
+
+Look, now `x` can be reused downstream:
+
+```{r}
+x - 2
+y = x * 2
+```
+
+## Grammar Structure 3: Evaluation of Functions
+
+A function has a **function name**, **arguments**, and **returns** a data type.
+
+::: {.callout-tip}
+## Execution rule for functions:
+
+Evaluate the function by its arguments, and if the arguments are functions or contains operations, evaluate those functions or operations first.
+
+The output of functions is called the **returned value**.
+:::
+
+```{r}
+sqrt(nchar("hello"))
+(nchar("hello") + 4) * 2
+```
+
+## Functions to read in data
+
+We are going to read in a Comma Separated Value (CSV) spreadsheet, that contains information about cancer cell lines.
+
+The first line calls the function `read.csv()` with a string argument representing the file path to the CSV file (we are using an URL online, but this is typically done locally), and the returned data type is stored in `metadata` variable. The resulting `metadata` variable is a new data type you have never seen before. It is a **data structure** called a **data frame** that we will be exploring next week. It holds a table of several data types that we can explore.
+
+We run a few functions on `metadata`.
+
+```{r}
+metadata = read.csv("https://github.com/caalo/Intro_to_R/raw/main/classroom_data/CCLE_metadata.csv")
+head(metadata)
+nrow(metadata)
+ncol(metadata)
+```
+
+If you don't know what a function does, ask for help:
+
+```{r}
+?nrow
+```
+
+## Tips on Exercises / Debugging
+
+Common errors:
+
+- Syntax error.
+
+- Changing a variable without realizing you did so.
+
+- The function or operation does not accept the input data type.
+
+- It did something else than I expected!
+
+
+Solutions:
+
+- Where is the problem?
+
+- What kind of problem is it?
+
+- Explain your problem to someone!
+
+
-
-## Video examples
-You may also want to embed videos in your course. If alternatively, you just want to include a link you can do so like this:
-
-Check out this [link to a video](https://www.youtube.com/embed/VOCYL-FNbr0) using markdown syntax.
-
-### Using `knitr`
-
-To embed videos in your course, you can use `knitr::include_url()` like this:
-Note that you should use `echo=FALSE` in the code chunk because we don't want the code part of this to show up. If you are unfamiliar with [how R Markdown code chunks work, read this](https://rmarkdown.rstudio.com/lesson-3.html).
-
-
-```{r, echo=FALSE}
-knitr::include_url("https://www.youtube.com/embed/VOCYL-FNbr0")
-```
-
-### Using HTML
-
-
-
-## File examples
-
-You can again use simple markdown syntax to just include a link to a file like so:
-
-[A file](https://www.bgsu.edu/content/dam/BGSU/center-for-faculty-excellence/docs/TLGuides/TLGuide-Learning-Objectives.pdf).
-
-Alternatively you can embed files like PDFs.
-
-### Using `knitr`
-
-```{r, fig.align="center", echo=FALSE, out.width="100%"}
-knitr::include_url("https://drive.google.com/file/d/1mm72K4V7fqpgAfWkr6b7HTZrc3f-T6AV/preview")
-```
-
-### Using HTML
-
-
-
-## Website Examples
-
-Yet again you can use a link to a website like so:
-
-[A Website](https://yihui.org)
-
-You might want to have users open a website in a new tab by default, especially if they need to reference both the course and a resource at once.
-
-[A Website](https://yihui.org){target="_blank"}
-
-Or, you can embed some websites.
-
-### Using `knitr`
-
-This works:
-
-```{r, fig.align="center", echo=FALSE}
-knitr::include_url("https://yihui.org")
-```
-
-
-### Using HTML
-
-
-
-
-If you'd like the URL to show up in a new tab you can do this:
-
-```
-LinkedIn
-```
-
-## Citation examples
-
-We can put citations at the end of a sentence like this [@rmarkdown2021].
-Or multiple citations [@rmarkdown2021, @Xie2018].
-
-but they need a ; separator [@rmarkdown2021; @Xie2018].
-
-In text, we can put citations like this @rmarkdown2021.
-
-## Stylized boxes
-
-Occasionally, you might find it useful to emphasize a particular piece of information. To help you do so, we have provided css code and images (no need for you to worry about that!) to create the following stylized boxes.
-
-You can use these boxes in your course with either of two options: using HTML code or Pandoc syntax.
-
-### Using `rmarkdown` container syntax
-
-The `rmarkdown` package allows for a different syntax to be converted to the HTML that you just saw and also allows for conversion to LaTeX. See the [Bookdown](https://bookdown.org/yihui/rmarkdown-cookbook/custom-blocks.html) documentation for more information [@Xie2020]. Note that Bookdown uses Pandoc.
-
-
-```
-::: {.notice}
-Note using rmarkdown syntax.
-
-:::
-```
-
-::: {.notice}
-Note using rmarkdown syntax.
-
-:::
-
-As an example you might do something like this:
-
-::: {.notice}
-Please click on the subsection headers in the left hand
-navigation bar (e.g., 2.1, 4.3) a second time to expand the
-table of contents and enable the `scroll_highlight` feature
-([see more](introduction.html#scroll-highlight))
-:::
-
-
-### Using HTML
-
-To add a warning box like the following use:
-
-```
-