Highly Experienced Instructors
Real World Applications
Cutting Edge Subject Matter
Continuous Learning with On-Demand Training Sessions and Workshops
Learn from some of the best and brightest minds in data science and AI on the Ai+ Training platform featuring:
- Hands-on Training
- Skills Assessments
- Certification Exams
- ODSC Conference Recordings
- Deep Learning Bootcamp
Half-Day Training | Deep Learning | Intermediate-Advanced
In this session, participants will be introduced to recent advances in audio-visual speech enhancement and separation, which has a variety of different applications…more details
Full-Day Training | Machine Learning | Beginner-Intermediate
This session is a hands-on introduction to Machine Learning in Python with scikit-learn. You will learn to build and evaluate predictive models on tabular data using the main tools of the Python data-science stack (Jupyter, numpy, pandas, matplotlib and scikit-learn)…more details
Full-Day Training | NLP | Deep Learning | Intermediate-Advanced
Being specialized in domains like computer vision and natural language processing is no longer a luxury but a necessity which is expected of any datascientist in today’s fast-paced world! With a hands-on and interactive approach, we will understand essential concepts in NLP along with extensive hands-on examples to master state-of-the-art tools, techniques and methodologies for actually applying NLP to solve real- world problems. We will leverage machine learning, deep learning and deep transfer learning to learn and solve popular tasks using NLP including NER, Classification, Recommendation \ Information Retrieval, Summarization, Classification, Language Translation, Q&A and Topic Models…more details
Half-Day Training | Machine Learning | Beginner
The objective of the session is to provide some basic understanding of Python as a language to be used for data processing. Python syntax is very readable and easy to work with, and its rich ecosystem of libraries makes it one of the most popular programming languages in the World.
We will see some common tools and characteristics of Python that are basic to analyse data, like how to import data from files and to generate results in multiple formats. We will also see some ways to speed-up the processing of data.
This workshop is aimed at people with little to no knowledge of Python, though some programming knowledge is required, even if it’s in a different language…more details
Half-Day Training | Quant Finance | Machine Learning | Intermediate
The rapid progress in machine learning (ML) and the massive increase in data availability has enabled novel approaches to quantitative investment and increased the demand for the application of data science to develop discretionary and automated trading strategies.
This workshop covers popular ML use cases for the investment industry. In particular, it focuses on how ML fits into the workflow of developing a trading strategy, from the engineering of financial features to the development of an ML model that generates tradable signals, the backtesting of a trading strategy that acts on these signals and the evaluation of its performance.
We’ll use common Python data science and ML libraries as well as Zipline, Pyfolio, and Alphalens. The code examples will be presented using jupyter notebooks and are based on the second edition of my book ‘Machine Learning for Algorithmic Trading’…more details
Half-Day Training | Big Data | Beginner
This tutorial will introduce you to the wonderful world of Bayesian data science through the lens of probabilistic programming in Python. In the first half of the tutorial, we will introduce the key concepts of probability distributions via hacker statistics, hands-on simulation, and telling stories of the data-generation processes. We will also cover the basics of joint and conditional probability, Bayes’ rule, and Bayesian inference, all through hands-on coding and real-world examples. In the second half of the tutorial, we will use a series of models to build your familiarity with PyMC3, showcasing how to perform the foundational inference tasks of parameter estimation, group comparison (for example, A/B tests and hypothesis testing), and arbitrary curve regression…more details
Workshop | Big Data | All Levels
In many data science ecosystems data frame is a pivotal object. It is not only very useful conceptually, but also ensures that data transformation operations can be performed efficiently. Therefore packages like data.table in R or pandas in Python are star players.
With the Julia language the situation is different because it gives you the speed out of the box. Therefore the DataFrames.jl package is designed to be a sidekick that conveniently supports your core data analysis pipeline. It has a more focused functionality than e.g. pandas, but at the same time it seamlessly integrates with the whole Julia data science ecosystem.
During this workshop, using hands-on examples, I will discuss the design principles behind DataFrames.jl and walk you through key functionalities provided by this package. All presented materials will be made available before the workshop in a blog post on https://bkamins.github.io/…more details
Tutorial | Machine Learning | Intermediate-Advanced
Advances in information extraction have enabled the automatic construction of large knowledge graphs (KGs) like DBpedia, YAGO, Wikidata of Google Knowledge Graph. Learning rules from KGs is a crucial task for KG completion, cleaning and curation. This tutorial presents state-of-the-art rule induction methods, recent advances, research opportunities as well as open challenges along this avenue...more details
Tutorials | Machine Learning | Intermediate
Automated machine learning is the science of building machine learning models in a data-driven, efficient, and objective way. It replaces manual trial-and-error with automated, guided processes. In this tutorial, we will guide you through the current state of the art in hyperparameter optimization, pipeline construction, and neural architecture search. We will discuss model-free blackbox optimization methods, Bayesian optimization, as well as evolutionary and other techniques. We will also pay attention to meta-learning, i.e. learning how to build machine learning models based on prior experience. Moreover, we will give practical guidance on how to do meta-learning with OpenML, an online platform for sharing and reusing machine learning experiments, and how to perform automated pipeline construction with GAMA, a novel, research-oriented AutoML tool in Python…more details
Workshop | Deep Learning | Intermediate-Advanced
CNNs, specialized neural networks for Computer Vision tasks, are used in sensitive contexts and exposed in the wild. While extremely accurate, they are also sensitive to imperceptible perturbations that can’t be detected by human eyes. For this reason, they have been targeted by hackers which implemented AI-based techniques for their malicious purposes. During this workshop we are going to learn some synthetic attacking techniques and a defence strategy to mitigate the effect of such attacks and make neural networks more robust to them, while at the same time keeping minimal impact on the accuracy of the model and implementation costs. We would also try to understand if Transformers applied to Computer Vision tasks are immune to Adversarial Attacks…more details
Workshop | Deep Learning | Intermediate
Learn the basics of building a PyTorch model using a structured, incremental and from first principles approach. Find out why PyTorch is the fastest growing Deep Learning framework and how to make use of its capabilities: autograd, dynamic computation graph, model classes, data loaders and more.
The main goal of this session is to show you how PyTorch works: we will start with a simple and familiar example in Numpy and “torch” it! At the end of it, you should be able to understand PyTorch’s key components and how to assemble them together into a working model.
We will use Google Colab and work our way together into building a complete model in PyTorch. You should be comfortable using Jupyter notebooks, Numpy and, preferably, object oriented programming…more details
Workshop | Machine Learning | Beginner-Intermediate
In this session, we will work through the basics of solving a classification-based machine learning problem using python and scikit-learn, and do a comparative study of two popular algorithms…more details
Tutorial | NLP | Deep Learning | Beginner-Intermediate
Have you wondered what is the technology behind the GPT models? In this talk, we are going to discuss the Transformer neural networks, introduced in 2017…more details
Workshop | Quant Finance | Intermediate-Advanced
This target of this workshop is twofold. On one hand, it is familiarizing attendees with mechanics of reinforcement learning (RL) applied to financial environments. On the other side, it aims to uncover key differences between popular RL applications (as playing video games) and financial ones, ignoring which inevitably will lead to losses of time and capital. With such insights and code boilerplates, attendees will be able to avoid harsh mistakes and implement environment-driven strategies faster…more details
Workshop | Responsible AI | Beginner
This workshop offers a gentle introduction to reproducible and elegantly formatted document generation with R Markdown. R Markdown presents a framework for reproducible workflows. It allows you to use multiple languages including R, Python, and SQL and helps you automate the production of HTML or PDF reports by relying on the power of Pandoc together with Lua-filters.
Participants will learn how to implement literate programming practices to make their workflows fully reproducible and produce automated reports. We will first cover the basics of narrative text and code integration. Then, we focus on working on a template that is fully optimized for two different output formats, HTML and PDF. While in the stage of explorative data analysis and with an eye on content only, our template allows you to produce beautiful HTML reports of your analyses, optimized for the interactive exploration of your data. While in the stage of dissemination and with an eye on the presentation of results, our template allows you to produce beautifully typeset PDF reports, ready to be circulated or published any time…more details
Workshop | Machine Learning | All Levels
By completing this workshop, you will develop an understanding of the different freely available RS data sources out there and open-source software tools that can be used for analysing these...more details
Tutorial | Quant Finance | Intermediate
This tutorial explores machine learning applications in economics and finance using TensorFlow 2. It starts by examining how TensorFlow and machine learning can be used to solve empirical and theoretical models in economics…more details
Workshop | MLOps | Intermediate-Advanced
Airflow is a leading open-source workflow orchestrator that offers a very wide range of possibilities. It can be integrated with Kubernetes using the KubernetesPodOperator to create pipelines that are extremely customizable. This is what we use to preprocess data and train ML models for PowerOP, Dataswati’s SAAS for optimizing food industry production lines…more details
Workshop | Big Data
By completing this workshop, you will develop an understanding of various vectors of AI risks to companies and be able to improve the governance inside your organization. Additionally, you will get hands-on experience on the problem of biased data and simulate an adversarial attack on a neural network model…more details
Workshop | Machine Learning | Responsible AI | Beginner
In the days where we have autonomous cars, drones, and automated medical diagnostics, we want to learn more about how to interpret the decisions made by the machine learning models. Having such information we are able to debug the models and retrain it in the most efficient way.
This talk is dedicated to managers, developers and data scientists that want to learn how to interpret the decisions made by machine learning models. We explain the difference between white and black box models, the taxonomy of explainable models and approaches to XAI. Knowing XAI methods is especially useful in any regulated company.
We go through the basic methods like the regression methods, decision trees, ensemble methods, and end with more complex methods based on neural networks. In each example, we use a different data set for each example. Finally, we show how to use model agnostic methods to interpret it and the complexity of the interpretability of many neural networks…more details
Workshop | Machine Learning | Beginner
General Data Protection Regulation (GDPR) is now in place. Are you ready to explain your models? This is a hands-on tutorial for beginners. I will demonstrate the use of open-source H2O platform (https://www.h2o.ai/products/h2o/) with both Python and R for automatic and explainable machine learning. Participants will be able to follow and build regression and classification models quickly with H2O AutoML. They will then be able to explain the model outcomes with various methods...more details
Workshop | MLOps | NLP | Intermediate
In this workshop we will explore the concept of MLOps Orchestration and how it can simplify the process of getting data science to production in any environment (multi-cloud, on-prem, hybrid), from the step of data collection and preparation (across real-time / streaming, historic, structured, or unstructured data), through automated model training to model deployment and monitoring. We will demonstrate how to drastically cut down the time and efforts needed to get data science to production. We’ll show how to map a business problem into an automated ML production pipeline and identify the right tools for the job, and ultimately how to run Al models in production at scale to accelerate business value with AI – all using open source technologies. The session will include a live demo and real customer case studies across use cases such as fraud prevention, real-time recommendation engines and NLP…more details
Workshop | MLOps | Intermediate
This session will explore and demonstrate how DataRobot’s MLOps can speed up deployment, monitor drift and accuracy, ensure governance and ongoing model lifecycle management, including how to do automation retraining and have challenger models in production…more details
Workshop | Life Sciences & Pharma | All Levels
A real-world scenario of applying ML in genomics will be discussed, where we shall build a predictor of a special type of DNA structures out of DNA sequence information alone…more details
Workshop | Machine Learning | All Levels
This will be a 90 minute workshop that will walk through how to set up, run and deploy a federated learning project from scratch…more details
Workshop | Responsible Ai | Machine Learning | Intermediate-Advanced
Recently, academics as well as policy makers have written many papers, on responsible data science / AI. Moreover, many open-source packages for bias dashboards or tools for `fairness’ have been proposed. This session aims to provide attendees a broad overview as well as the specific technical background to use the available ` fairness’ tools. In addition, a governance framework describing the precise responsibilities of data scientists will be discussed…more details
Workshop | Machine Learning | Quant Finance | Beginner
Unlike some of my prior presentations and tutorials that covered both statistical and neural network-based models for time series analysis, this talk will be introductory in nature and will focus on the discussion of a couple of workhorse statistical time series models that are frequently applied to solving time series forecasting problems…more details
Tutorial | Quant Finance | Beginner-Intermediate
This tutorial aims to demystify ML by uncovering its underlying mathematics and showing how to apply ML methods to real-world financial data…more details
Tutorial | MLOps | All Levels
Machine learning has evolved from the experimenting stage to real-world production systems with a need for automated quality assurance and delivery, reproducibility and deployment consistency…more details
Workshop | Deep Learning | Beginner-Intermediate
This workshop will walk you through how to convert mathematical concepts into code to build AI models. At the end of the workshop, you’ll learn how to write code from scratch to do the magic i.e. generate images and deepfake video…more details
Workshop | Machine Learning | Intermediate-Advanced
In this workshop you will learn when and why federated learning should be used, basic algorithms for implementing it, as well as more advanced ones covering a variety of use-cases. Towards the end of the workshop participants will be offered a hands-on experience of training a federated model together…more details
Workshop | Deep Learning | NLP | All Levels
Over the past few years speech synthesis or text-to-speech (TTS) has seen rapid advances thanks to deep learning. As anyone who owns a voice assistant will know, artificial voices are becoming more and more natural and convincing. The good news is you can recreate this impressive technology yourself, using high quality open-source tools.
In this workshop, we’ll learn all about TTS and create a custom speech synthesis system from scratch. We’ll take a look at the development of TTS systems up to the present day, investigate the challenges that researchers are still grappling with, and walk through and end-to-end example of creating a deep learning-based TTS system – including data preparation, training, inference and evaluation. This workshop doesn’t require any prior knowledge of TTS or deep learning…more details
Workshop | NLP | Intermediate-Advanced
Transformers have taken the AI research and product community by storm. We have seen them advancing multiple fields in AI such as NLP, Computer Vision, Robotics. In this talk, I will be giving some background in Conversational AI, NLP and Transformers based Large Scale Language Models such as BERT and GPT-3…more details
Tutorial | Machine Learning | Beginner-Intermediate
Faces are a fundamental piece of photography, and building applications around them has never been easier with open-source libraries and pre-trained models. In this tutorial, we’ll help you understand some of the computer vision and machine learning techniques behind these applications. Then, we’ll use this knowledge to develop our own prototypes to tackle tasks such as face detection (e.g. digital cameras), recognition (e.g. Facebook Photos), classification (e.g. identifying emotions), manipulation (e.g. Snapchat filters), and more…more details