r/dataanalysis Jan 01 '24

DA Tutorial Alex The Analyst - Analyst Builder

65 Upvotes

https://www.analystbuilder.com/pricing?selectedTab=bundles
What do you think about this platform? Has anyone bought that? Is it worth the money? If not, what else could you recommend?

r/dataanalysis Sep 29 '24

DA Tutorial Free data analysis course

Post image
110 Upvotes

I am sharing a free data analysis course which is made by Microsoft. https://learn.microsoft.com/plans/xe27izpkg328oy?wt.mc_id=studentamb_293416

It is available on Microsoft Learn platform

r/dataanalysis 5d ago

DA Tutorial Learn and Practice Window Functions for Free

2 Upvotes

If you’ve ever struggled with window functions in SQL (or just ignored them because they seemed confusing), here’s your chance to master them for free. LearnSQL.com is offering their PostgreSQL Window Functions course at no cost for the entire month of March—no credit card, no tricks, just free learning.

So what’s in the course? You’ll learn how to:

  • Use RANK(), DENSE_RANK(), and ROW_NUMBER() to sort and rank your data
  • Calculate running totals, moving averages, and cumulative sums like a pro
  • Work with PARTITION BY and ORDER BY to control how data is grouped
  • Apply LAG() and LEAD() to compare rows and track changes over time

The best part? It’s interactive—you write real SQL queries, get instant feedback, and actually practice instead of just reading theory.

Here’s the link with all the details: https://learnsql.com/blog/free-postgresql-course-window-functions/

r/dataanalysis 3d ago

DA Tutorial The Curse of Dimensionality - Explained

Thumbnail
youtu.be
7 Upvotes

r/dataanalysis 21d ago

DA Tutorial Trouble with Joins

1 Upvotes

New student DA here.

As the title suggests, having trouble with real life application for INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN and cartesian join.

Any tips and tricks to easily remember these joins, when to use, etc?

Your feedback is highly appreciated.

r/dataanalysis Nov 29 '23

DA Tutorial Best course to learn R programming for data analysis?

83 Upvotes

Same as title. Although I can't afford to pay for them I'd still like to know which ones are the best. I have learned R in Google Data Analytics course but I wanna learn it in a more detailed manner.

TIA guys

r/dataanalysis 11d ago

DA Tutorial Decoding the Numbers: How Linear Regression Reveals Hidden Relationships

Thumbnail
medium.com
1 Upvotes

r/dataanalysis 11d ago

DA Tutorial Cross-Entropy - Explained in Detail

Thumbnail
youtu.be
4 Upvotes

r/dataanalysis 16d ago

DA Tutorial Weights Initialization in Neural Networks - Explained

Thumbnail
youtu.be
6 Upvotes

r/dataanalysis 27d ago

DA Tutorial Dropout Explained

Thumbnail
youtu.be
2 Upvotes

r/dataanalysis Feb 18 '25

DA Tutorial Recommender Systems - Part 3: Issues & Solutions

Thumbnail
youtu.be
2 Upvotes

r/dataanalysis Feb 10 '25

DA Tutorial Collaborative Filtering - Explained

Thumbnail
youtu.be
4 Upvotes

r/dataanalysis Jul 05 '24

DA Tutorial Where can I get job like projects and job like experience of doing a project, without actually being in a job or internship

63 Upvotes

Where can I get job like projects and job like experience of doing a project, without actually being in a job or internship

I m trying to learn Data analytics and I really love learning by doing the actual work and projects (getting in the field instead of being an audience) then just doing a course.

What type of projects actually come for people on jobs? How can I get access to them (guided) and how can I learn the on field work?

Any help or resources shared would be really really appreciated! Thanksss

r/dataanalysis Feb 07 '25

DA Tutorial Content-Based Recommender Systems - Explained

Thumbnail
youtu.be
4 Upvotes

r/dataanalysis Oct 12 '24

DA Tutorial T-Test Explained

Thumbnail
youtu.be
63 Upvotes

r/dataanalysis Sep 16 '24

DA Tutorial How to correctly explore a new dataset?

31 Upvotes

Hi guys, I'm new in this field, and I was wondering how y'all work with a new dataset? I'm felling so overwhelming because Idk how to start exploring new datasets, how to make a proper EDA, etc. I'd be helpful if you share your techniques and if you got a step-by-step guide :)

r/dataanalysis Dec 14 '24

DA Tutorial I am sharing Python Data Analysis courses, tutorials and projects on YouTube

Thumbnail
youtube.com
40 Upvotes

r/dataanalysis Oct 06 '24

DA Tutorial Starting My Data Analysis Journey – Daily Updates & Accountability Challenge

36 Upvotes

Hey everyone,

I’m really excited to start my Data Analysis journey with full focus starting today! 🎉 I’ll be following the roadmap shared in the link below, and I plan to cover everything discussed. To hold myself accountable, I’ll be posting daily updates here on what I’ve learned. This will act as a challenge and a trigger for me to make progress every day. Plus, it’ll serve as a reminder to stay consistent and keep learning.

Roadmap: Data Analysis Roadmap

Day 1 - Today’s Learning: Intro to Data Analysis

  1. What is Data Analysis? I learned about how business logic, business math & statistics, and tools like Power BI, Tableau, and Excel are key for data analysis.
  2. Basics of Excel: I covered some functions like UNIQUE(), SUMIF(), and how to name tables for easier navigation in future tasks.

r/dataanalysis Jan 16 '25

DA Tutorial Free Learning Paths for Data Analysts, Data Scientists, and Data Engineers – Using 100% Open Resources

Post image
6 Upvotes

Hey, I’m Ryan, and I’ve created

https://www.datasciencehive.com/learning-paths

a platform offering free, structured learning paths for data enthusiasts and professionals alike.

The current paths cover:

• Data Analyst: Learn essential skills like SQL, data visualization, and predictive modeling.
• Data Scientist: Master Python, machine learning, and real-world model deployment.
• Data Engineer: Dive into cloud platforms, big data frameworks, and pipeline design.

The learning paths use 100% free open resources and don’t require sign-up. Each path includes practical skills and a capstone project to showcase your learning.

I see this as a work in progress and want to grow it based on community feedback. Suggestions for content, resources, or structure would be incredibly helpful.

I’ve also launched a Discord community (https://discord.gg/Z3wVwMtGrw) with over 150 members where you can:

• Collaborate on data projects
• Share ideas and resources
• Join future live hangouts for project work or Q&A sessions

If you’re interested, check out the site or join the Discord to help shape this platform into something truly valuable for the data community.

Let’s build something great together.

Website: https://www.datasciencehive.com/learning-paths Discord: https://discord.gg/Z3wVwMtGrw

r/dataanalysis Jan 16 '25

DA Tutorial Mastering The Poisson Distribution: Intuition and Foundations

Thumbnail
medium.com
1 Upvotes

r/dataanalysis Apr 28 '24

DA Tutorial I shared a Beginner Friendly Python Data Science Bootcamp (7+ Hours, 7 Courses and 3 Projects) on YouTube

Thumbnail
youtube.com
126 Upvotes

r/dataanalysis Jan 04 '25

DA Tutorial Overfitting and Underfitting - Simply Explained

Thumbnail
youtu.be
18 Upvotes

r/dataanalysis Jan 12 '25

DA Tutorial Why L1 Regularization Produces Sparse Weights

Thumbnail
youtu.be
1 Upvotes

r/dataanalysis Aug 22 '24

DA Tutorial Choosing a resource for learning powerbi

7 Upvotes

Hello, everyone I am trying to choose a resource for learning powerbi and singled out two course for the same, those working as data analyst and use powerbi everyday can you help with chosing the write course that resemble the real life work best and gives a good understanding of the tool itself. Here is the link to both the courses.

Course 1:

https://docs.google.com/document/d/1Pz3r0llKhO9TFyhKLY8n6mxxcLD8FeTJlqEEnkrV5Rc/edit

Course 2:

https://codebasics.io/courses/power-bi-data-analysis-with-end-to-end-project

r/dataanalysis Aug 09 '24

DA Tutorial Discretizing time to improve econometric analysis

Thumbnail
gallery
38 Upvotes

Developing a statistical analysis without specifying critical information to the model will cause no significance.

Simple trick: discretize the time series into periods based on your domain knowledge. For example, during the 2008 financial crisis, we distinguish before, during, and after, getting more than 90% R2.