3 Kinds of data science conferences: Which one is right for you?


Data science conferences provide you with a great way to boost your skills and meet new industry professionals. However, since there are so many of them, it can be very hard to figure out which are the right ones to attend. That being said, it’s important to plan and figure out which are the right conferences you need to check out this year.

Why should you attend data science conferences?

The primary benefit is that you get to learn how to enter the field and you can also adapt to the ever-changing trends. Not only that, but you get to make connections, increase your employability and this is a field that expands a lot faster when compared to others.

Unlike other conferences, the data science conferences are designed to help you achieve real business outcomes. They enable you to find solutions that will eventually make your business grow and reach new heights in the long run.

There are some downsides to this too. For example, data science conferences can be quite expensive to attend. That’s why we made it easy for you to figure out what kinds of data science conferences you need to attend, as you don’t want to go overboard with the expenses on this.

DataScienceGo

What makes DacaScienceGo amazing is the fact that it helps you with networking, presentations and maximizing value, all of that at $399. This is by far one of the best data science conferences if you want to transition to data science from other fields. For that amount you get access to 3 days of panels, training sessions and immersive talks that will act as a guideline for your journey. Practitioners can meet other experts and beginners will find it a great place to learn.

Unlike large data science conferences, DSGO is a smaller and more personal conference. It allows current data scientists to showcase their journey and it offers newcomers information on how they can reach the industry, what challenges they can encounter and what they can expect in the long run from something like this. This conference also helps newcomers to meet their idols and find new peers.

Strata

Strata is more expensive, it starts at around $795, and it’s a presentation based mid-range conference. It’s one of the most established data conferences in the world, and it covers a variety of things from data engineering and architecture to machine learning, law, cyber security, ethics, big data to visualization and so on.

Experts share various data case studies and best practices for newcomers and other professionals alike. It’s a good conference for a newcomer, however it’s also geared toward experts, executives and analysists.

Transforming Data With Intelligence (TDWI)

TDWI is a conference that starts at $2,235. It’s an expensive, course-based conference that will help you understand the future of data science as well as teach you important data science tasks and rules. You will figure out how to innovate thanks to AI and machine learning, manage data security and users, all while democratizing the analytics efforts.

The main benefit of TDWI is that you have lots of data science and big data courses. These include the Enterprise Dashboard Design guide, Ensuring a successful journey to the cloud, TDWI analytics fundamentals and TDWI business intelligence and analytics architecture.

However, these courses are mostly for consultants, executives, data scientists, BI architects, analytics team members and project managers. It’s not a newcomer-friendly conference, it’s mostly focused on people that already work in the industry and want to improve their current skills and knowledge.

These are the types of data science conferences that you need to attend this year. If you want to grow as a data science professional, you should consider attending these conferences right away. However, it all comes down to your own needs, knowledge, and budget. Some of them are more accessible than others and they also have a different focus. So you just have to study the situation as you figure out which are the best options for you!

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