# Where to Find Information on Data Structures: A Complete Guide to the Every Programmer Should Know Repository

> Discover curated data structures resources for programmers. Find free courses, textbooks, and tutorials in the mtdvio/every-programmer-should-know repository's README.

- Repository: [MTDV/every-programmer-should-know](https://github.com/mtdvio/every-programmer-should-know)
- Tags: how-to-guide
- Published: 2026-02-26

---

**You can find curated information on data structures in the [`README.md`](https://github.com/mtdvio/every-programmer-should-know/blob/main/README.md) file of the `mtdvio/every-programmer-should-know` repository, specifically in the Data Structures section located at lines 56-62, which links to free courses, textbooks, and interactive tutorials.**

The `mtdvio/every-programmer-should-know` repository serves as a curated "resource handbook" for software developers. If you are looking for reliable information on data structures, this repository aggregates high-quality educational materials into a single, accessible location within its master documentation file.

## Locating the Data Structures Section in README.md

All information on data structures resides in the central [`README.md`](https://github.com/mtdvio/every-programmer-should-know/blob/main/README.md) file at the repository root. The maintainers have organized this file into thematic subsections, with Data Structures receiving its own dedicated heading.

### Direct Link to the Resource List

You can jump directly to the relevant content using this permalink to lines 56-62:

```markdown
https://github.com/mtdvio/every-programmer-should-know/blob/master/README.md#L56-L62

```

This anchor contains the complete list of recommended courses, books, and interactive tools for learning data structures.

## Types of Data Structure Resources Available

The curated list categorizes resources by learning style and depth. Each entry targets a specific aspect of data structure education, from visual introductions to rigorous mathematical foundations.

### Interactive Courses and Video Lectures

**UC Berkeley Data Structures Course (Sp19)** offers a full semester-length curriculum with video lectures and coding assignments. This resource provides hands-on practice with implementations in a structured academic format.

```markdown
https://sp19.datastructur.es/

```

### Online MOOCs and Structured Learning

For self-paced study, the repository lists two major platforms:

- **Foundations of Data Structures** on edX (IIT Bombay) – A structured path with quizzes and peer review components
- **Coursera Data Structures** – A specialized course focusing on algorithmic applications of core structures

### Reference Books and Visual Guides

**Hello Algo** provides concise visual explanations of each data structure with accompanying code snippets. This resource is particularly effective for developers who learn best through diagrams and step-by-step visualizations.

```markdown
https://www.hello-algo.com/en/chapter_preface/about_the_book/

```

### Foundational Mathematical Texts

**Mathematics for Computer Science** (Lehman) supplies the mathematical underpinnings—set theory, combinatorics, and proof techniques—essential for understanding complexity analysis and correctness proofs for data structures.

```markdown
https://people.csail.mit.edu/meyer/mcs.pdf

```

## Practical Examples Using Recommended Resources

The following examples demonstrate how to apply the knowledge gained from the repository's recommended resources. These snippets illustrate concepts covered in the listed courses and books.

### Binary Search Tree Implementation

This Python example reflects the type of implementation practice found in the UC Berkeley course and Hello Algo visualizations:

```python
class Node:
    def __init__(self, key):
        self.key = key
        self.left = self.right = None

def insert(root, key):
    if not root:
        return Node(key)
    if key < root.key:
        root.left = insert(root.left, key)
    else:
        root.right = insert(root.right, key)
    return root

# After building the tree, you can visualize it using the Hello Algo

# interactive tool at https://www.hello-algo.com/visualise

```

### Accessing Course Materials Programmatically

This bash example shows how you might interact with the edX platform to retrieve course structure information for the Foundations of Data Structures course:

```bash

# Example of retrieving course metadata from edX API

# (Actual endpoint requires authentication)

curl -L "https://courses.edx.org/api/courses/v1/courses/iitbombayx/CS213.1x/3T2015" \
  -H "Accept: application/json" \
  -o course_structure.json

# Parse the JSON to extract weekly module names for study planning

cat course_structure.json | jq '.blocks[] | select(.type=="chapter") | .display_name'

```

## Summary

- The `mtdvio/every-programmer-should-know` repository consolidates information on data structures in its [`README.md`](https://github.com/mtdvio/every-programmer-should-know/blob/main/README.md) file, specifically at lines 56-62.
- Resources include interactive university courses (UC Berkeley), MOOCs (edX, Coursera), visual guides (Hello Algo), and mathematical foundations (Lehman).
- All listed materials are free and curated for quality, covering implementations, complexity analysis, and theoretical underpinnings.
- No other files in the repository contain data structure content; the README serves as the single source of truth.

## Frequently Asked Questions

### What specific file contains the data structures information?

The information resides exclusively in the [`README.md`](https://github.com/mtdvio/every-programmer-should-know/blob/main/README.md) file at the root of the `mtdvio/every-programmer-should-know` repository. The Data Structures subsection is located at lines 56-62 of this file, containing all curated links and resource descriptions.

### Are the resources listed free to access?

Yes, all resources referenced in the Data Structures section are freely available. This includes the UC Berkeley course materials, edX audit tracks, Coursera free enrollment options, the Hello Algo online book, and the MIT Mathematics for Computer Science PDF.

### What types of learning materials are included?

The curated list spans four categories: interactive video courses with coding assignments (UC Berkeley), structured MOOCs with certification options (edX, Coursera), visual reference books with code snippets (Hello Algo), and foundational mathematical texts for complexity analysis (Lehman).

### How can I contribute to this resource list?

While the source analysis focuses on consumption rather than contribution mechanics, the repository follows standard GitHub open-source practices. You would typically fork the repository, edit the [`README.md`](https://github.com/mtdvio/every-programmer-should-know/blob/main/README.md) file to add vetted resources, and submit a pull request following the project's contribution guidelines.