Data Science Blogathon - 13
About the Event
Blogathon - 14 is currently live! Register Now: https://bit.ly/3kG42Op
Data Science Blogathon returns with a lot of fanfare!
Special Diwali Offer - We are extending the Blogathon registration date till 3rd of November! Register Now and submit your article to win exciting prizes!
Having published over 1500 articles, we continue to be the talk of the town! Over 500 authors from all over the world are a part of our thriving community. Are you ready to join this international community?
What are the Prizes on offer?
Choose the content you want to create and win for each published article - there's no minimum views threshold this time!
Submission Type | Minimum Length of Text | Topic | Base Reward for Creators Club Members | Base Reward for non-members |
Article | 1000 words | Deep Learning, CV, NLP, Data Engineering, MLOps | INR 1,800(≅USD 24) | INR 1,500(≅USD 20) |
Any Other Topic | INR 1,200(≅USD 16) | INR 1,000(≅USD 13) | ||
Guide | 2500 words | No Constraints(please refer to suggestions below) | INR 3,000(≅USD 40) | Not Applicable |
* Publish 3 or more articles in any blogathon and automatically become a part of the Anaytics Vidhya Creators Club to avail exciting benefits and prizes!
* Note that the article will have to be technical and code-based in nature to be eligible for the above special categories. Listicles or career articles will not count.
* All International payments will be made via Paypal
What's at stake?
- The top 3 Articles will be judged based on the number of unique pageviews
- The top 3 Guides will be judged by the editorial team
Submission Type | Rank | Winners Prize |
Articles | ![]() |
INR 10,000(≅USD 133) |
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INR 5,000(≅USD 66) | |
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INR 3,000(≅USD 40) | |
Guides* | ![]() |
INR 7500(≅USD 100) each |
* 3 Guides (Chosen by Editors)
And that's not all! More Prizes!
Submission Type | Views | Bonus Rewards |
Article and Guide | 5000 to 15000 | INR 1,000(≅USD 13) |
>15000 | INR 2,000(≅USD 26) |
A New Submission Category - Guides!
As mentioned above, we are introducing a new type of submission this time, called "Guides". Since we receive multiple entries for Guides, only one Guide per topic will be published.
Guide Topics | Guide Topics | Guide Topics | Guide Topics |
End-to-End Machine Learning Model using Julia | A Comprehensive Guide on Building an ETL Pipeline for Beginners | A Detailed Case Study using Geospatial Analysis | A Complete Guide on ggplot |
A Comprehensive Guide on Building Bots using Python | A Complete Guide on Kubernetes | A Detailed Study on Covid-19 Vaccinations data | How to deal with Sparse Datasets |
Building an End-to-End Multiclass Text Classification Model | A Comprehensive Guide on using Django for Data Science | Building an End-to-End Polynomial Regression Model | A Comprehensive Guide on Recommendation Engines |
A Comprehensive Guide on Building Chatbots | A Comprehensive Guide on using AWS for Data Science | End-to-End Predictive Analysis on Zomato | A Comprehensive Guide on Graph Neural Networks |
A Comprehensive Guide on ML Interpretability Techniques and Tools | A Comprehensive Guide on using RedShift | A Comprehensive Guide on Replication in Data Engineering | A Comprehensive Guide on Causal Inference |
A Comprehensive Guide on Federated Learning | A Detailed Guide on SQL Query Optimisation | A Comprehensive Guide on Sharding in Data Engg. | A Comprehensive Guide on Neo4j |
A Comprehensive Guide on Markov Chain | A Complete Guide on using MongoDB for Data Science | A Comprehensive Guide on Partitioning in Data Engg. | An End-to-end Guide on Anomaly Detection |
A Complete Guide on PowerBI | A Comprehensive Guide on Feature Engineering | A Comprehensive Guide on Microsoft Excel for Data Analysis | A Comprehensive Guide on using AzureML |
A Comprehensive Guide on using KNIME | A Comprehensive Guide on Optuna | A Comprehensive Guide on Machine Learning for Mobile Devices | A Comprehensive Guide on using Flask for Data Science |
Here is an example of a Guide: K Means Clustering | K Means Clustering Algorithm in Python
Feel free to explore any topic of your choice though - the only restriction is that it should be as comprehensive as possible and should be of a minimum of 2500 words in length.
How do I Participate?
To enter the competition, just press the register button above. Once the competition starts on October 9th, please head over to https://editor.analyticsvidhya.com/ and start writing. It's that simple!
Note that it takes us up to 36 hours to review and provide feedback for each article. And once you see ‘Published’ on the Editor, give it up to 6 hours for the article to reflect on the Analytics Vidhya blog.
What are the important dates & deadlines?
Oct 9, 2021 | Nov 3, 2021 11:59 P.M. IST (GMT + 5:30 hrs) |
Nov 7, 2021 11:59 P.M. IST (GMT + 5:30 hrs) |
Nov 7, 2021 11:59 P.M. IST (GMT + 5:30 hrs) |
Nov 9, 2021 |
Registration Begins | Registration Ends | Submission Ends | Views will be counted till this date | Winners Announcement |
Note: We update the leaderboard twice a day. There is no set time for the update per se. But check back in the afternoon and late evening to see the latest views.
Participate in Discussion
Registration Details
Total registered
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Spaces You Can Join
Frequently Asked Questions
Find the answers for the most frequently asked questions
Participants benefit from one-on-one feedback, publication on a respected platform, recognition from a global audience, and monetary rewards for each published article. Additionally, the top articles receive special rewards.
Each article must be original, and pass plagiarism and not AI generated content checks. You can submit multiple articles as long as each is distinct. Proper citation of all references and image sources is mandatory.
There are no specific requirements to register for the hackathon, although it is recommended to have some basic knowledge of the relevant topics, such as Data Science, Machine Learning, or Deep Learning, along with proficiency in a coding language, preferably Python.
In the Blogathon, an article typically explores a specific topic or idea within Data Science or Generative AI and is required to be at least 1000 words long. A guide, on the other hand, is a more comprehensive resource, covering all aspects of a particular subject in data science, and must be at least 2500 words long. Guides aim to serve as a one-stop resource, providing detailed insights and practical applications, whereas articles might focus on narrower or more specific topics.
Depending on the type of competition, you can participate individually or in a team.
Multiple submissions of the same article are prohibited and could lead to disqualification. Articles failing to meet the required length, originality, or citation standards will be rejected.
AVCC is a community for authors who have had three or more articles published in the Blogathons. Members benefit from monetary rewards for each published article and get the opportunity to showcase their work to a larger audience.
You can access the problem statement under the "Problem Statement" tab once the Hackathon is live.
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