Add images to enhance course documentation; include visuals for homework, deadlines, resources, and community support to improve engagement and clarity.

kavaivaleri · kavaivaleri · commit 94493d0d6f41 · 2025-09-29T18:27:06.000+02:00
diff --git a/assets/images/ml-zoomcamp/ml-zoomcamp-youtube.png b/assets/images/ml-zoomcamp/ml-zoomcamp-youtube.png
diff --git a/ml-zoomcamp-2025/assignments-and-scoring.md b/ml-zoomcamp-2025/assignments-and-scoring.md
@@ -12,18 +12,36 @@ Homework is created fresh for every cohort and its purpose is to help you check
 
 Assignments are published under `cohorts/2025/{module}` in the GitHub repository of the course. Once ready, the submission form will be shared in Slack.
 
+<div align="center">
+  <img src="/assets/images/ml-zoomcamp/ml-zoomcamp-homework.png" alt="Alt text" width="80%">
+</div>
+
 The process is simple: solve the tasks locally, publish your solution to a public GitHub repo (or similar), and submit the link through the form.
 
 Each homework comes with a strict deadline listed [on the schedule](https://courses.datatalks.club/ml-zoomcamp-2025/). After the deadline passes, the form closes.
 
 ## 2. Staying Updated with Deadlines and Announcements
 
-All homework and project deadlines are published on the [course platform](https://courses.datatalks.club/ml-zoomcamp-2025/). Announcements are always posted in Slack, Telegram, and the DataTalksClub newsletter. If you don't receive the DataTalksClub newsletter, you may have unsubscribed from it.
+All homework and project deadlines are published on the [course platform](https://courses.datatalks.club/ml-zoomcamp-2025/).
+
+<div align="center">
+  <img src="/assets/images/ml-zoomcamp/ml-zoomcamp-course-platform-schedule.png" alt="Alt text" width="80%">
+</div>
+
+Announcements are always posted in Slack, Telegram, and the DataTalksClub newsletter. If you don't receive the DataTalksClub newsletter, you may have unsubscribed from it.
+
+<div align="center">
+  <img src="/assets/images/ml-zoomcamp/ml-zoomcamp-slack.png" alt="Alt text" width="80%">
+</div>
 
 ## 3. Homework for Certification
 While homework assignments are **optional for certification**, they're essential for solidifying your understanding of each module's concepts. Homework participation contributes to your overall course score and leaderboard position.
 
 ## 4. Leaderboard
 Submissions also appear on the [leaderboard](https://courses.datatalks.club/ml-zoomcamp-2025/leaderboard), which adds a fun competitive element. The leaderboard is optional, but many students find it motivating.
 
+<div align="center">
+  <img src="/assets/images/ml-zoomcamp/ml-zoomcamp-leaderboard.png" alt="Alt text" width="80%">
+</div>
+
 You can also gain extra points by sharing your learning publicly with the hashtag `#mlzoomcamp` and tagging Alexey Grigorev or DataTalksClub.
diff --git a/ml-zoomcamp-2025/certification.md b/ml-zoomcamp-2025/certification.md
@@ -8,6 +8,10 @@ nav_order: 4
 
 ## 1. What You Need to Pass
 
+<div align="center">
+  <img src="/assets/images/ml-zoomcamp/ml-zoomcamp-github-structure.png" alt="Alt text" width="80%">
+</div>
+
 Earning your ML Zoomcamp certificate requires completing a specific combination of projects rather than achieving a particular grade. You must **pass 2 out of 3 available projects**, giving you flexibility in choosing your path. You can complete either the midterm project plus the final capstone project, or the final capstone project plus a second capstone project.
 
 For each project you submit, you're required to **complete peer reviews** by evaluating 3 of your fellow students' projects. This peer review process is mandatory and helps reinforce your learning while contributing to the community.
diff --git a/ml-zoomcamp-2025/getting-help.md b/ml-zoomcamp-2025/getting-help.md
@@ -8,6 +8,14 @@ nav_order: 5
 
 Before reaching out for help in Slack, make it a habit to check the comprehensive [FAQ website](https://datatalks.club/faq/machine-learning-zoomcamp.html) first. This resource contains answers to the most common questions from previous cohorts and will often solve your problem immediately.
 
+<div align="center">
+  <img src="/assets/images/ml-zoomcamp/ml-zoomcamp-faq.png" alt="Alt text" width="80%">
+</div>
+
 When you encounter problems, the way you ask for help determines the quality of responses you'll receive. Start by checking the [FAQ website](https://datatalks.club/faq/machine-learning-zoomcamp.html) and searching through previous Slack conversations for similar issues. This preliminary research often reveals that your question has already been addressed.
 
+<div align="center">
+  <img src="/assets/images/ml-zoomcamp/ml-zoomcamp-slack.png" alt="Alt text" width="80%">
+</div>
+
 When you do need to ask for help, provide context that enables others to assist you effectively. Include specific error messages and relevant code snippets (use ```python code blocks), mention your operating system and Python version, and share a link to your GitHub repository so helpers can understand your complete setup. For example, instead of asking "My code doesn't work," provide: "I'm getting `ModuleNotFoundError: No module named 'sklearn'` on macOS with Python 3.11 when running the linear regression notebook from Module 2. Here's my repository: [link]." This approach not only gets you better answers but also helps other students who might face similar challenges.
diff --git a/ml-zoomcamp-2025/getting-started.md b/ml-zoomcamp-2025/getting-started.md
@@ -10,10 +10,22 @@ nav_order: 0
 
 Start by visiting the [ML Zoomcamp GitHub repository](https://github.com/DataTalksClub/machine-learning-zoomcamp) and **starring it** ⭐. All course materials are in this repository, with each module having its own folder (for example, `01-intro` or `03-classification`). Cohort-specific homework and deadlines are located in `cohorts/2025`.
 
-The lectures are pre-recorded and available in the **YouTube playlist**, so you can watch them whenever it suits you. Occasionally, additional workshops or updated implementation videos are released—there will be additional announcements if this happens. If nothing is announced, you can assume all necessary materials are already available.
+<div align="center">
+  <img src="/assets/images/ml-zoomcamp/ml-zoomcamp-github-structure.png" alt="Alt text" width="80%">
+</div>
+
+The lectures are pre-recorded and available in the [YouTube playlist](https://www.youtube.com/playlist?list=PL3MmuxUbc_hIhxl5Ji8t4O6lPAOpHaCLR), so you can watch them whenever it suits you. Occasionally, additional workshops or updated implementation videos are released—there will be additional announcements if this happens. If nothing is announced, you can assume all necessary materials are already available.
+
+<div align="center">
+  <img src="/assets/images/ml-zoomcamp/ml-zoomcamp-youtube.png" alt="Alt text" width="80%">
+</div>
 
 Finally, locate and bookmark the [FAQ Website](https://datatalks.club/faq/machine-learning-zoomcamp.html). This comprehensive resource contains answers to the most frequently asked questions from previous cohorts. Make it a habit to check this document before asking questions in Slack, as your question has likely been answered before.
 
+<div align="center">
+  <img src="/assets/images/ml-zoomcamp/ml-zoomcamp-faq.png" alt="Alt text" width="80%">
+</div>
+
 ## 2. Course Structure and Flexibility
 
 The course has **no regular live sessions** except for occasional intro streams, supporting self-paced learning.
@@ -28,4 +40,12 @@ Before diving into the coursework, ensure you have the necessary technical found
 
 Connect with the vibrant ML Zoomcamp community to enhance your learning experience. After registering for the course, you'll receive an invitation to the **Slack Workspace** via email. Join the workspace and navigate to the "machine-learning-zoomcamp" channel, which serves as your primary support and Q&A platform throughout the course.
 
+<div align="center">
+  <img src="/assets/images/ml-zoomcamp/ml-zoomcamp-slack.png" alt="Alt text" width="80%">
+</div>
+
 Consider also joining the **Telegram Channel** for course announcements. While optional, it's highly recommended for receiving important updates and staying connected with course developments.
+
+<div align="center">
+  <img src="/assets/images/ml-zoomcamp/ml-zoomcamp-telegram.png" alt="Alt text" width="80%">
+</div>
diff --git a/ml-zoomcamp-2025/resources.md b/ml-zoomcamp-2025/resources.md
@@ -10,22 +10,42 @@ nav_order: 7
 
 The [GitHub repository](https://github.com/DataTalksClub/machine-learning-zoomcamp) contains all course materials and serves as the central hub for the course.
 
+<div align="center">
+  <img src="/assets/images/ml-zoomcamp/ml-zoomcamp-github-structure.png" alt="Alt text" width="80%">
+</div>
+
 ## YouTube Playlist
 
 The [YouTube playlist](https://www.youtube.com/playlist?list=PL3MmuxUbc_hIhxl5Ji8t4O6lPAOpHaCLR) contains all course lectures.
 
+<div align="center">
+  <img src="/assets/images/ml-zoomcamp/ml-zoomcamp-youtube.png" alt="Alt text" width="80%">
+</div>
+
 ## Course Platform
 
 The [course platform](https://courses.datatalks.club/ml-zoomcamp-2025/) is a dedicated platform for submitting homework and accessing course materials.
 
+<div align="center">
+  <img src="/assets/images/ml-zoomcamp/ml-zoomcamp-course-platform-schedule.png" alt="Alt text" width="80%">
+</div>
+
 ## Slack
 
 The [Slack workspace](https://datatalks.club/slack.html) is a community-driven platform for discussing the course and getting help from fellow learners and instructors.
 
+<div align="center">
+  <img src="/assets/images/ml-zoomcamp/ml-zoomcamp-slack.png" alt="Alt text" width="80%">
+</div>
+
 ## Telegram
 
 The [Telegram channel](https://datatalks.club/telegram.html) is for course announcements only. If you don't receive the newsletter, you may have unsubscribed from it.
 
+<div align="center">
+  <img src="/assets/images/ml-zoomcamp/ml-zoomcamp-telegram.png" alt="Alt text" width="80%">
+</div>
+
 ## Newsletter
 
 The [Newsletter](https://datatalks.club/newsletter.html) provides course announcements. Here's the [newsletter archive](https://us19.campaign-archive.com/home/?u=0d7822ab98152f5afc118c176&id=97178021aa).
@@ -34,6 +54,11 @@ The [Newsletter](https://datatalks.club/newsletter.html) provides course announc
 
 The [FAQ](https://datatalks.club/faq/machine-learning-zoomcamp.html) is a comprehensive resource containing answers to the most frequently asked questions from previous cohorts. Make it a habit to check this document before asking questions in Slack, as your question has likely been answered before.
 
+<div align="center">
+  <img src="/assets/images/ml-zoomcamp/ml-zoomcamp-faq.png" alt="Alt text" width="80%">
+</div>
+
+
 ## Community Notes
 
 At [datatalkclub.com/notes](https://datatalkclub.com/notes), you can both contribute your own notes and benefit from previous participants' detailed explanations.
diff --git a/ml-zoomcamp-2025/success.md b/ml-zoomcamp-2025/success.md
@@ -14,6 +14,10 @@ Most importantly, approach every project as a **portfolio piece** that should be
 
 Share your progress regularly on LinkedIn and Twitter using the #mlzoomcamp hashtag, and tag Alexey Grigorev and DataTalks.Club in your posts. The **leaderboard system** at [courses.datatalks.club/ml-zoomcamp-2025/leaderboard](https://courses.datatalks.club/ml-zoomcamp-2025/leaderboard) awards points for homework completion, FAQ contributions, and resource sharing.
 
+<div align="center">
+  <img src="/assets/images/ml-zoomcamp/ml-zoomcamp-leaderboard.png" alt="Alt text" width="80%">
+</div>
+
 Consider writing blog posts about concepts you've mastered or challenges you've overcome. Examples include "Understanding Cross-Validation in Module 4" or "My Journey Deploying a FastAPI Model." Posts about struggles like "3 Deployment Failures That Taught Me Docker Basics" are often more valuable than success stories. When you feel confident in a topic, answer questions in Slack—teaching others solidifies your own knowledge.
 
 ## Study Strategy
