Data Science Dojo strongly believes in learning and growing together as a community, for that reason last year we conducted several community events for you all. Although all the events were helpful in their way, there are top 10 events that received the highest number of sign-ups, are:
1. SQL crash course for beginners
When learning data science, students typically focus on Python or R for data analysis and machine learning. On the job though, data is usually stored in a database, and that data can either be accessed through a business intelligence tool or directly using SQL. This crash course is intended for beginners with no prior experience in SQL
2. MLOps crash course for beginners
Data scientists at the start of their careers often have the misconception that their job will be largely focused on training and improving models in a Jupyter notebook. The reality is that most data science value is created outside of a notebook. This crash course is intended for data scientists with basic knowledge of developing machine learning models in a Jupyter notebook setting.
3. Python crash course for excel users
If you’re an Excel user looking to level up your analytics skills, Python is a great choice for repeatable processes, compelling visualizations, and robust visualizations. And while learning to code may seem too difficult, your Excel knowledge gives you a significant head start. This introduction is intended for Excel users with no prior knowledge of Python.
4. Power BI crash course for beginners
The webinar will help you get started with Microsoft’s Power BI by teaching you how to prepare your data, analyze it and build insightful visualizations on the interactive data visualization software Power BI Desktop.
5. Redis crash course for Artificial Intelligence & Machine Learning
Redis — the super-fast in-memory database, is being increasingly used for machine learning: from caching, messaging, and fast data ingestion, to vector similarity search and online feature stores. This crash course is for ML and Data Engineers looking to learn more about deploying real-time AI/ML at scale, as well as Data Scientists making the transition from theory to applied Data Science.
6. From data to the dashboard: Make an interactive model
Students typically create their portfolios out of simple, clean datasets while projects in the professional space will require steps beyond the initial creation and evaluation of a model. This hands-on skill-building webinar is for starting and intermediate data science students with a basic knowledge of Python.
7. Deploying Machine Learning models with Flask and Docker
What happens after we train a model in a Jupyter notebook? It’s time to deploy it! This talk will help you learn about putting ML models into production and deploying it as a web service.
8. Effective data storytelling as a Data Scientist in the industry
In this talk, you’ll look at a couple of common mistakes that data practitioners often make in creating presentations for the business. Things as using a complicated diagram or including the output of coefficients.
9. AI & ML workflows with Kubernetes
In this session, you’ll explore how to incorporate data science and AI/ML into Kubernetes development workflows, taking advantage of the platform’s openness and rich ecosystem. Using well-known open-source tools for Data Science such as Jupyter Notebooks and TensorFlow, we will explore different strategies to accelerate and automate ML workloads with Kubernetes.
10. Web Scraping with Python and BeautifulSoup
The number of websites on the internet is estimated to be around 2 billion. Web scraping turns the entire world wide web into your data set. In this webinar, you will learn how to scrape a website using the BeautifulSoup package in Python.
Stay tuned for upcoming 2023 informative community events
All 63 events hosted by Data Science Dojo in 2022, were conducted by professionals and subject experts. We tried our best to cover all crucial areas and critical topics of Data Science, AI, and ML.
We have always worked to nurture & establish our community; we believe in learning & growing together. We intend to hold on to our purpose of “making data science available to everyone” in the upcoming years.
We have planned out lots of exciting learning opportunities for our audience in 2023, which we are very excited to share with you all. Meanwhile, comment below to let us know topics you want to hear about from industry experts in 2023.
