8 ODSC Europe Training Sessions to Boost Your Data Science Career
Ready to fill in some of your knowledge gaps and build new skills? Check out the hands-on training and bootcamp sessions that are coming to ODSC Europe next month.
Training
AI-Powered Algorithmic Trading with Python
Dr. Yves J. Hilpisch | The AI Quant | CEO The Python Quants & The AI Machine, Adjunct Professor of Computational Finance
This session will cover the essential Python topics and skills that will enable you to apply AI and Machine Learning (ML) to Algorithmic Trading. You’ll learn how to use the Oanda trading API (via a demo account) to retrieve data, to stream data, and to place orders. Building on this, you’ll formulate and backtest ML-based trading and transform it into an online trading algorithm that is deployed for real-time trading on the Oanda trading platform.
Introduction to Data Analysis Using Pandas
Stefanie Molin | Software Engineer, Data Scientist, Chief Information Security Office | Bloomberg LP | Author of Hands-On Data Analysis with Pandas
This session will equip you with the knowledge you need to effectively use pandas to make working with data easier.
Pandas makes it possible to work with tabular data and perform all parts of the analysis from collection and manipulation through aggregation and visualization. You will also take a look at matplotlib and seaborn.
NLP Fundamentals
Leonardo De Marchi | VP of Labs | Thomson Reuters
Laura Skylaki, PhD | Manager of Applied Research | Thomson Reuters Labs
This course will cover Natural Language Processing fundamentals, such as pre-processing techniques,tf-idf, embeddings, and more. It will be followed by practical coding examples, in Python, to teach how to apply the theory to real use cases. You’ll leave this session with the basic tools and knowledge you need to solve real-world problems and understand cutting-edge NLP topics.
Generative AI
Leonardo De Marchi | VP of Labs | Thomson Reuters
In this workshop, you’ll explore how artificial intelligence can be used to generate creative outputs and to inspire technical audiences to use their skills in new and creative ways. You will also go through a series of code exercises designed to give participants hands-on experience working with AI models to generate creative outputs. Some of the exercises we will cover include:
- Generating poetry using NLP models like LSTM and Transformer.
- Creating digital art using computer vision models like Deep Dream and StyleGAN.
- Generating music using GANs and other AI models.
- Using reinforcement learning to generate creative outputs that match certain criteria or goals.
sktime — Python Toolbox for Machine Learning with Time Series
Franz Kiraly, PhD | Founder and Core Developer of sktime
This session will explore sktime — a unified framework for machine learning with time series. sktime covers multiple time series learning problems, including time series transformation, classification, and forecasting, among others. You will learn about how you can identify these problems, what their key differences are, and how they are related. You will also learn how to use, combine, tune, and evaluate different algorithms on real-world data sets.
Bootcamp
Introduction to Python for Data Analysis
Leonidas Souliotis, PhD | Senior Data Scientist | AstraZeneca
In this workshop, you will get acquainted with the pandas library, which is the most widely used package for reading, analyzing and exporting datasets in Python. You will also learn how to visualize many kinds of tabular data using the plotnine package, along with some tips and tricks on how to make your visualizations stand out. Lastly, you will have the opportunity to make predictions and make decisions using data, based on basic statistical methods.
Python Fundamentals
Philip Tracton | Instructor, Principal IC Design Engineer | UCLA Extension, Medtronic
In this class, students will install Anaconda Python and Jupyter Labs. Using this Jupyter Lab interface you’ll learn about the basics of Python programming. Topics will include built-in data structures, functions, looping, decisions, and importing other libraries.
Introduction to Machine Learning
Julia Lintern | Director of Data Science | Gartner
Join this session to build on your foundation of math and coding knowledge to develop a basic understanding of the most popular machine learning algorithms used in the industry today. You will explore questions like: What are the different types of ML algorithms? What is Overfitting and how can we avoid it? Why is XGBoost consistently outperform other algorithms? This session will cover both Supervised and Unsupervised models.
Conclusion
These are just a few of the sessions that you will find at the can’t-miss conference of the summer. Register now and lock in our limited-time offer of 40% off any in-person or virtual pass to ODSC Europe 2023.
Originally posted on OpenDataScience.com
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