An ODSC speaker is someone with proven data science expertise and a strong capability to present the latest languages, tools, and models used in data science and AI for business. These individuals are committed to sharing innovative ideas and contributing to the growth of open source software.
Since its inception, the Open Data Science Conference has highlighted the significant contributions presenters make to the field of data science. Thanks to their participation attendees have come to expect the highest quality talks, workshops and training sessions.
First Open Call for Speakers – January 15th , 2018
End of First Round of Call for Speakers – March 25, 2018
Second Open Call for Speakers– April 16, 2018
Please be advised that the First Open Call for Speakers is the best opportunity to get your session accepted for ODSC Europe. The Second Open Call for Speakers is a rolling call for submissions and depends upon any focus areas the speaker committee feels more quality speakers are needed.
You can submit a presentation for ODSC conference or for “Accelerate AI” summit which is ODSC’s business summit.
Accelerate AI is ODSC’s business summit for executives and business professionals. Co-located with ODSC, the summit will bring together top industry executives and CxOs to help you understand how AI and data science will transform your business.
All submissions will received notification, regardless of status, by February 1st. All proposals submitted after this deadline will receive a response within three weeks.
Proposals will be considered for the following types of presentations:
Format for Technical Sessions
Format for Business Sessions
Here are some helpful guidelines to consider for your proposal:
Your title should grab the interest of attendees and concisely tell attendees what your session is about.
The recommended abstract must be at least 250 words. However, ensure your abstract is succinct and speaks to both the topic and context of your presentation. This abstract will be use on an online speaker page, mobile app and other online marketing platforms. The description must also explain what the attendee will learn from your presentation.
Be advised that the speaker committee reserves the right to reject any talk at any time, if the presentation does not match the abstract and stated intent.
ODSC attracts a highly-educated audience of data science practitioners. The topic difficulty level you select must consider the quality of our audience in addition the complexity of the data science languages and tools you will discuss.
Beginner: These sessions help attendees learn the fundamentals of a subject area.
Intermediate: These sessions help attendees increase their knowledge of a subject area.
Advanced: These sessions help attendees increase their already advanced knowledge of a subject area.
On the submission form, you will be asked to explain why the particular topic difficulty level was selected.
Workshop and Training sessions require a demonstrable track record in data science instruction. Individuals who qualify, include those who have experience teaching at a university, boot camp, or educational organization as well as core contributors to the data science field.
Workshop and training sessions will undergo a secondary review process of the session’s curriculum.
In keeping with our motto, “The Future of AI is Here,” original presentations and materials are preferred in contrast to recycled presentations.
Product or services pitches are expressly prohibited by ODSC. When you submit, you are obligated to confirm your proposal is not a sales pitch for a proprietary software or an indirect sales channel for a company. If you are looking for an exposure opportunity for your company, we have many other opportunities during the conference for that. Please email us at firstname.lastname@example.org for more details.
If you know someone who would be a great addition to speak at our audience please, let us know at email@example.com
If you are a business looking to present to our data science audience please see our partner section.
Natural Language Processing
Data Science at Scale
Data Science Managment
Data Science Workflow
Python, Jupyter Notebooks
R programming, Julia, Scala, Stan
Apache Spark, MLlib, Streaming
Tensorflow, MXNet, Caffe, CNTK
Scikit-learn, Theano, Shogun, Pylearn2
Azure ML, Amazon ML,H20.ai, Cloud ML
Neo4J, D3.js, R-Shiny
Hadoop, Apache Storm, Apache Flink, Kafka
Data Science Research
Data Science for Good
200+ Speakers over 4 days