CORPORATE AI TRAINING
Data Science Assessment and Training from World-Renowned Instructors
Assessment
We help determine your organization’s AI path to success with industry insights and executive level briefings.
Leading Instructors
We conduct a pre-training assessment to align team training needs with organizational goals to deliver a custom program in collaboration with our training partners.
AI Success
Our training partners, consisting of some of the world’s leading data scientists, provide in-person hands-on training and workshops at our facilities or yours.
What Our Courses Cover
We cover the latest in data science focus areas, topics, and tools
Focus Areas
Deep Learning
Machine Learning
Natural Language Processing
Data Visualization
Data Wrangling
Data Science at Scale
Data Analytics
Topics
Recommendation Systems
Churn Detection
Conversational AI
Building Data Science Teams
Artificial Intelligence
Speech Recognition
Unsupervised Learning
Tools
Tensorflow 2.0, Keras, TFX, PyTorch
Python, Pandas, SciPi, Numy, scikit-learn
R programming, R Packages, R-Shiny, Tidyverse
Apache Spark, MLFlow, KubeFlow, Kafka
Neo4J, D3.js, Plotly
Key Reasons to Use ODSC Training
Upskill Your Team
We help unlock your business and technical teams potential. Our upskill programs in analytics, data engineering, and data science are designed to bolster your company’s growth.
Your team will earn a Certificate of Completion after completing a post-event assessment.
The skills and knowledge acquired have immediate impact on your organization.
The Best of the Best
Unlike traditional training programs, ODSC draws from our incredibly talented roster of trainers and instructors. These are globally renowned experts that have received the highest ratings from our participants.
The hands-on training sessions are run by some of the top instructors and practitioners in data science.
Many instructors are authors or core contributors to the top open source frameworks in deep learning and machine learning.
Custom Programs
Each industry and company has unique requirements. We bring not only data science skills to your team but also deep domain expertise to ensure our programs fit with your business objectives.
Each team had different training needs. Our expansive list of instructors can meet those needs.
Our instructors are practicing data scientists with deep domain experience across a variety of industries including finance, healthcare, retail, and many others.
Live and On-Demand
Upcoming Live Virtual Training
Live on-line
September 1, 8 & 15, 2020
Learn how to utilize data storytelling to drive change and improve project outcomes
Live on-line
October 14, 2020
Put the theory into practice and learn from the acclaimed author, instructor, and data scientist, Dr. Kirk Borne
Live on-line
September 30, 2020
Improve your knowledge of one of the top 5 must have DATA skills in 2020
Live on-line
October 22, 2020
Learn how to use Python to create striking visualizations that incorporate movement
Live on-line
TBD, 2020
Get hands-on practice with Python and Pandas under the guidance of a top-ranked instructor
“ The content was interesting, at just the right level of detail (not too over heads for people new to the topic but not so basic as to be a waste of time), and engaging. I loved the style and flow of the course, with lots of visuals and examples to keep us engaged. This is the best workshop/training/presentation I have attended in a long time
Indi Matthew, Analytics Consultant, USA
Swami
Upskill Your Team at the Leading Data Science Conference
Live on-line
September 17-19, 2020
Discover your team’s potential with hands-on training, workshops, and tutorials led by top practitioners and leading experts
Live on-line
October 27-30, 2020
Help your team meet their potential with training sessions, workshops, and tutorials in the cutting-edge topics and tools
“ ODSC is the best data science event on the planet. There are other events that cover special topics, or industries, etc.,
but ODSC is comprehensive the conference to engage, to build, to develop, and learn ” – Kirk Borne – Principal Data Scientist and Executive Advisor at Booz Allen Hamiltom
Contact Us
Get in touch and we can discuss your team’s training needs
Some Teams We’ve Hosted at ODSC
Meet Some of Our Leading Experts
We Partner with Over 30 World-Class Instructors
Andreas Mueller, PhD
Andreas Mueller is a Principal Research SDE at Microsoft (previously Columbia, NYU, Amazon), and author of the O’Reilly book “Introduction to machine learning with Python”, describing a practical approach to machine learning with python and scikit-learn. He is one of the core developers of the scikit-learn machine learning library, and has been co-maintaining it for several years. Andreas is also a Software Carpentry instructor.
Automatic DataFrame Profiling and Visualization for Machine Learning(Talk)
Dr. Jon Krohn
Jon Krohn is Co-Founder and Chief Data Scientist at the machine learning company Nebula. He authored the book Deep Learning Illustrated, an instant #1 bestseller that was translated into seven languages. He is also the host of SuperDataScience, the data science industry’s most listened-to podcast. Jon is renowned for his compelling lectures, which he offers at leading universities and conferences, as well as via his award-winning YouTube channel. He holds a PhD from Oxford and has been publishing on machine learning in prominent academic journals since 2010.
Deep Learning with PyTorch and TensorFlow(Training)
NLP with GPT-4 and other LLMs: From Training to Deployment with Hugging Face and PyTorch Lightning(Training)
On Demand Course Offerings
We Have Over 200+ Courses in Our Catalog
Previous Machine Learning Training Sessions
introduction to Data Science
Focus Area: Data Science Type: Hands-on Workshop Duration 2 to 3 Days Customizable: Yes
Course Description:
Curious about Data Science? Self-taught on some aspects, but missing the big picture? Well you’ve got to start somewhere and this session is the place to do it. This session will cover, at a layman’s level, some of the basic concepts of data science. In a conversational format, we will discuss: What are the differences between Big Data and Data Science – and why aren’t they the same thing? What distinguishes descriptive, predictive, and prescriptive analytics? What purpose do predictive models serve in a practical context? What kinds of models are there and what do they tell us? What is the difference between supervised and unsupervised learning? What are some common pitfalls that turn good ideas into bad science? During this session, attendees will learn the difference between k-nearest neighbor and k-means clustering, understand the reasons why we do normalize and don’t overfit, and grasp the meaning of No Free Lunch.
Fundamentals of Machine Learning
Focus Area:Machine Learning Type: Hands-on Workshop Duration 2 to 3 Days Customizable: Yes
Course Description:
Machine learning has become an indispensable tool across many areas of research and commercial applications. From text-to-speech for your phone to detect the Higgs boson, machine learning excels at extracting knowledge from large amounts of data. This talk will give a general introduction to machine learning, as well as introduce practical tools for you to apply machine learning in your research. We will focus on one particularly important subfield of machine learning, supervised learning. The goal of supervised learning is to “learn” a function that maps inputs x to an output y, by using a collection of training data consisting of input-output pairs. We will walk through formulating a problem as a supervised machine learning problem, creating the necessary training data and applying and evaluating a machine learning algorithm. This workshop should give you all the necessary background to start using machine learning yourself.
Beginner to Intermediate Machine Learning in Python
Focus Area: Machine Learning Type: Hands-on Workshop Duration 3 to 5 Days Customizable: Yes
Course Description:
Scikit-learn is a machine learning library in Python, that has become a valuable tool for many data science practitioners. This workshop will go beyond the basics and show how to effectively evaluate and tune algorithms. We will also discuss the most important machine learning algorithms that you’re likely to see in practice, how and when to use them, and some details about how they work internally. The session will focus on linear models for classification and regression and tree-based models, including random forests.
Programming with Data: Foundations of Python and Pandas
Focus Area: Machine Learning, Python Type: Hands-on Workshop Duration 3 to 5 Days Customizable: Yes
Course Description:
Whether in R, MATLAB, Stata, or Python, modern data analysis, for many researchers, requires some kind of programming. The preponderance of tools and specialized languages for data analysis suggests that general purpose programming languages like C and Java do not readily address the needs of data scientists; something more is needed.
In this training, you will learn how to accelerate your data analyses using the Python language and Pandas, a library specifically designed for interactive data analysis. Pandas is a massive library, so we will focus on its core functionality, specifically, loading, filtering, grouping, and transforming data.
Having completed this course, you will understand the fundamentals of Pandas, be aware of common pitfalls, and be ready to perform your own analyses.
What you’ll learn and how you can apply it
- Use the Split-Apply-Combine technique to calculate grouped summary statistics like mean, median, and standard deviation on your data.
- Load data from flat files and native Python data structures and compute on them using Pandas.
- Avoid common pitfalls and “gotchas” in Pandas by understanding the conceptual underpinnings common to most data manipulation libraries and environments.
Programming with Data: Advanced Python and Pandas
Focus Area: Machine Learning, Python Type: Hands-on Workshop Duration 3 to 5 Days Customizable: Yes
Course Description:
Do you use Pandas in your daily workflow but wonder if the advanced features of the library could accelerate your analyses? In this training, you will learn how to solve complex data manipulation problems using Python and advanced features of Pandas.
We will principally study two classes of problems, then learn how to solve them with Pandas.
First, we review data manipulations that would be challenging to achieve without a SQL execution engine or a significant investment in custom tooling. Second, we review problems that are difficult to solve with SQL. These include merging and joining datasets with appropriate handling of missingness, reshaping data from wide to long format, and manipulating time series.
Having completed this course, you will be ready to use advanced Pandas functionality in your own analyses.
What you’ll learn and how you can apply it
- Perform advanced merges including combining daily data with irregular frequency data, e.g. one-time events.
- Transforming data between “wide” and “long” formats and generating pivot tables.
- Filter, upsample, downsample, and compute on time series data.
Introduction to Natural Language Processing and Text Analytics
Focus Area: Machine Learning, Python Type: Hands-on Workshop Duration 1 to 3 Days Customizable: Yes
Course Description:
Data is the new oil and unstructured data, especially text, images and videos contain a wealth of information. However, due to the inherent complexity in processing and analyzing this data, people often refrain from spending extra time and effort in venturing out from structured datasets to analyze these unstructured sources of data, which can be a potential gold mine.
Natural Language Processing (NLP) is all about leveraging tools, techniques, and algorithms to process and understand natural language-based unstructured data – text, speech and so on.Being specialized in domains like computer vision and natural language processing is no longer a luxury but a necessity that is expected of any data scientist in today’s fast-paced world!
With a hands-on and interactive approach, we will understand essential concepts in NLP along with the extensive case- studies and hands-on examples to master state-of-the-art tools, techniques, and frameworks for actually applying NLP to solve real-world problems. We leverage Python 3 and the latest and best state-of-the-art frameworks including NLTK, Gensim, SpaCy, Scikit-Learn, TextBlob, Keras and TensorFlow to showcase our examples. You will learn a fair bit of machine learning as well as deep learning in the context of NLP during this bootcamp.
The intent of this workshop is to make you a hero in NLP so that you can start applying NLP to solve real-world problems. We start from zero and follow a comprehensive and structured approach to make you learn all the essentials in NLP. We will be covering the following aspects during the course of this workshop with hands-on examples and projects!
Basics of Natural Language and Python for NLP tasks
Text Processing and Wrangling
Text Understanding – POS, NER, Parsing
Text Representation – BOW, Embeddings, Contextual Embeddings
Text Similarity and Content Recommenders
Text Clustering
Topic Modeling
Text Summarization
Sentiment Analysis – Unsupervised & Supervised
Text Classification with Machine Learning and Deep Learning
Multi-class & Multi-Label Text Classification
Deep Transfer Learning and it’s promise
Applying Deep Transfer Learning – Universal Sentence Encoders, ELMo and BERT for NLP tasks
Generative Deep Learning for NLP
Advanced Statistics in R: Modeling and Analytics
Focus Area: Data Analytics, Statistics, R Type: Hands-on Workshop Duration 2 to 3 Days Customizable: Yes
Course Description:
We focus on the available methods for implementing machine learning algorithms in R, and will examine some of the underlying theory. We will explore several models which includes linear regression, elastic net, tree-based models, clustering, bootstrapping, and cross-validation.
Text Mining and Sentiment Analysis in Practice with R
Focus Area: Machine Learning, R Type: Hands-on Workshop Duration 2 to 3 Days Customizable: Yes
Course Description:
Machine Learning in R
Focus Area: Machine Learning, R Type: Hands-on Workshop Duration 2 to 3 Days Customizable: Yes
Course Description:
Modern statistics has become almost synonymous with machine learning, a collection of techniques that utilize today’s incredible computing power. This two-part course focuses on the available methods for implementing machine learning algorithms in R, and will examine some of the underlying theory behind the curtain. We start with the foundation of it all, the linear model and its generalization, the glm. We look how to assess model quality with traditional measures and cross-validation and visualize models with coefficient plots. Next we turn to penalized regression with the Elastic Net. After that we turn to Boosted Decision Trees utilizing xgboost. Attendees should have a good understanding of linear models and classification and should have R and RStudio installed, along with the `glmnet`, `xgboost`, `boot`, `ggplot2`, `UsingR` and `coefplot` packages.
Linear Models
Learn about the best fit line
Understand the formula interface in R
Understand the design matrix
Fit Models with `lm`
Visualize the coefficients with `coefplot`
Make predictions on new data
Generalized Linear Models
Learn about Logistic Regression for classification
Learn about Poisson Regression for count data
Fit models with `glm`
Visualize the coefficients with `coefplot`
Model Assessment
Compare models
`AIC`
`BIC`
Cross-validation
Learn the reasoning and process behind cross-validation
Elastic Net
Learn about penalized regression with the Lasso and Ridge
Fit models with `glmnet`
Understand the coefficient path
View coefficients with `coefplot`
Boosted Decision Trees
Learn how to make classifications (and regression) using recursive partitioning
Fit models with `xgboost`
Make compelling visualizations with `DiagrammeR
Advanced Statistics in R : Modeling and Analytics
Focus Area: Machine Learning, R Type: Hands-on Workshop Duration 1 to 3 Days Customizable: Yes
Course Description:
We focus on the available methods for implementing machine learning algorithms in R, and will examine some of the underlying theory. We will explore several models which includes linear regression, elastic net, tree-based models, clustering, bootstrapping and cross-validation.
An Introduction to Reinforcement learning
Focus Area: Machine Learning Type: Hands-on Workshop Duration 1 to 3 Days Customizable: Yes
Course Description:
In this course we will explore Reinforcement Learning, starting from its fundamentals and ending with Deep Reinforcement Learning algorithms.
We will use OpenAI gym to try our RL algorithms. OpenAI is a non-profit organisation that wants to open source all their research on Artificial Intelligence. To foster innovation OpenAI created a virtual environment, OpenAi gym, where it’s easy to test Reinforcement Learning algorithms.
In particular we will start with some popular techniques like Multi Armed Bandit, going through Markov Decision Processes and Dynamic Programming.
Afterwards we will also explore other RL frameworks and more complex concepts like Policy gradients methods and Deep Reinforcement learning, which recently changed the field of Reinforcement Learning. In particular we will see Actor Critic models and Proximal Policy Optimizations that allowed openai to beat some of the best Dota players.
Previous Deep Learning Training Sessions
Fundamentals of Deep Learning
Focus Area: Deep Learning Type: Hands-on Workshop Duration 3 to 5 Days Customizable: Yes
Fundamentals of Deep Learning
Course Description:This course is an introduction to deep learning, a branch of machine learning concerned with the development andapplication of modern neural networks. Deep learning algorithms extract layered high-level representations of data ina way that maximizes performance on a given task. For example, asked to recognize faces, a deep neural networkmay learn to represent image pixels first with edges, followed by larger shapes, then parts of the face like eyes andears, and, finally, individual face identities. Deep learning is behind many recent advances in AI, including Siri’sspeech recognition, Facebook’s tag suggestions and self-driving cars.We will cover a range of topics from basic neural networks, convolutional and recurrent network structures, deepunsupervised and reinforcement learning, and applications to problem domains like speech recognition and computervision.
Prerequisites: a strong mathematical background in calculus, linear algebra, and probability & statistics
Customizable: Cours can be to your specific industry
Introduction to Deep Learning with Tensorflow 2.0 & Keras
Focus Area: Deep Learning, NLP Type: Hands-on Workshop Duration 1 to 3 Days Customizable: Yes
Course Description:
Relatively obscure a few short years ago, Deep Learning is ubiquitous today across data-driven applications as diverse as machine vision, natural language processing, and super-human game-playing.
This Deep Learning primer brings the revolutionary machine-learning approach behind contemporary artificial intelligence to life with interactive demos featuring TensorFlow 2, the major, cutting-edge revision of the world’s most popular Deep Learning library.
To facilitate an intuitive understanding of Deep Learning’s artificial-neural-network foundations, the essential theory will be introduced visually and pragmatically. Paired with tips for overcoming common pitfalls and hands-on Python code run-throughs provided in straightforward Jupyter notebooks, this foundational knowledge empowers you to build powerful state-of-the-art Deep Learning models.
Lesson 1: The Unreasonable Effectiveness of Deep Learning
Training Overview
Introduction to Neural Networks and Deep Learning
The Deep Learning Families and Libraries
Lesson 2: Essential Deep Learning Theory
The Cart Before the Horse: A Shallow Neural Network in TensorFlow 2
Learning with Artificial Neurons
TensorFlow Playground—Visualizing a Deep Net in Action
Lesson 3: Deep Learning with TensorFlow 2
Revisiting our Shallow Neural Network
Deep Nets in TensorFlow
Convolutional Neural Networks in TensorFl
Deep Learning for Natural Language Processing
Focus Area: Deep Learning, NLP Type: Hands-on Workshop Duration 1 to 3 Days Customizable: Yes
Course Description:
Deep Reinforcement Learning
Focus Area: Deep Learning Type: Hands-on Workshop Duration 1 to 3 Days Customizable: Yes
Course Description:
Previous Business Training Sessions
Managing machine learning Data Analytics for decision making
Focus Area: Analytics Type: Hands-on Workshop Duration 3 to 5 Days Customizable: Yes
Course Description:
In this course we will explore some of the challenges that managers face implementing and maintaining machine learning solutions.
Topics will include:
– Build, integrate, improve and manage a team to deliver machine learning solutions.
– Estimate the business impact of your systems.
– Infrastructure requirements and solutions available.
– Evaluate and monitor the models’ performance.
The goal of the course is to cover the main pain points that organizations face deploying machine learning solutions.
Data Analytics for Decision Making
Focus Area: Data Visualization & Analytics Learning Type: Hands-on Workshop Duration 2 to 3 Days Customizable: Yes
Course Description:
Introduction
We will see examples of what analytics, how it is used for decision making and why a modern business needs it.
Work Organization
In this session we will see how it’s possible to organise the team and the work of a company’s analytical functions. We will see how the work is organised on large internet companies (+450 million users) and some strategies to get the best results, looking at both within the team and outside it.
Tools and Infrastructure
In this session we will explore modern infrastructure and tools for different analytical needs. We will see how to create a strategy and a roadmap to implement.
Informed decision making
We will see how it’s possible to estimate the future impact of possible actions and how it’s possible to estimate the actual impact afterwards. We will look at a project example from a top sports team and from an online business. We will use statistics, AB test and data visualizations. We will also see how we can create a data driven culture also in non-technical departments and how to balance it with other needs of the company.
Predictive analytics
We will define the main metrics that a business needs to look at and which statistical methods to use to forecast them. We will also look at machine learning models, how it’s possible to use them to automatically make decisions and to extract insights from them.
Fundamentals of Data Analytics
Focus Area: Data Visualization & Analytics Learning Type: Hands-on Workshop Duration 2 to 3 Days Customizable: Yes
Course Description:
Data analytics and visualization is revolutionizing business across all industry verticals.
Our mission of this course is to prepare people to solve real business problems. Our courses put concepts first, and treat tools and technology as an enabler, not the core focus. We take the key concepts and best practices of analytics, visualization and design thinking based on the latest academic research, and present them in a clear, concise and actionable format.We bring the concepts to life with realistic, business relevant examples based on our consulting experience. All our courses are hands on, and get participants applying the concepts to real problems right away. We ensure that all participants walk away at the end of each course with new outputs they have created themselves, which they can apply to real business problems the next day
We can work with you to tailor the content for your organization, and to use your real business data in our examples. Of course, we are happy to sign a non-disclosure agreement and maintain absolute confidentiality.Our team of analysts and consultants can provide a thorough make over your existing reports and dashboards in advance of the course, applying industry best practices. Our instructor will then walk your teams through the reasoning behind the changes, and how to implement similar improvements in the future.A fully online version of our most popular course. It will include detailed instructional videos, and online knowledge check tests. This can also be integrated with face to face delivery or Webex to include a workshop with an instructor to consolidate the concepts.
Data Visualization and Dashboard Design
Focus Area: Data Visualization & Analytics Learning Type: Hands-on Workshop Duration 2 to 3 Days Customizable: Yes
Course Description:
Advanced Visualization and Dashboard Design is aimed at the professional who already possesses fundamental data visualization and data storytelling skills. A natural continuation point from Data Storytelling for Business, this course provides participants with the skills needed to produce stunning, understandable business dashboards and graphs. Taught using a variety of visualization tools, the course covers the keys to designing for interactivity and drill down effects. The course also covers less commonly used but valuable visualization methods, including methods for visualizing networks and flows. Dashboard design is covered in detail, with participants creating a dashboard ‘makeover’ during the class practical workshop.
Data Story Telling for business
Focus Area: Data Visualization & Analytics Learning Type: Hands-on Workshop Duration 2 to 3 Days Customizable: Yes
Course Description:
We know charts don’t tell the story on their own – this course will also provide examples and practice in incorporating a storytelling approach to sharing data. You’ll practice how to identify your audience, select appropriate metrics, relationships, and visuals to keep your audience engaged with your data story. Most importantly, you’ll learn how to create a data story that is easily accessible and actionable for your audience.
In our interactive workshops, you will work on your own real business data sets and reports, and walk away from the course with immediate improvements to impress your managers and stakeholders.
Course Objectives
- Provide participants with a grounding in the four ‘keys to data storytelling’ – Audience, Data, Visuals and Narrative
- Provide participants with a methodology for selecting the right chart for a particular set of data
- Provide participants with industry best practices for the most common chart types (including the bar, line and pie chart)
- Provide participants with an understanding of the “Gestalt” principles of perception and how they can be used to focus audience attention
- Provide participants with an overview of the scientific research surrounding chart design, including work from Edward Tufte
Training FAQs
What type of training do you provide?
Our comprehensive training catalog contains over 60 courses. We ensure our courses cater to all abilities, from beginner to advanced, and from technical to business, including the following training:
Introductory Level Training
- R and Python programming
- Machine Learning
- Deep Learning
- Natural Langage Processing
- Text Analytics
- Data Visualization
- Data Wrangling
- Statistics and fundamental Mathematics
Intermediate to Advanced Level Training
We also offer intermediate to advanced level training that builds on software development, machine learning, and deep learning. Course included
- Recommendation systems
- Churn detection
- Reinforcement learning
- NLP and NLU pertained models
- Model trust and Explainability
- Machine Vision
- Speech Recognition
- Machine Learning Workflow
AI Framework Training
Companies are successfully leveraging Open Source Data Science platforms to develop cutting edge AI projects. We offer courses in:
- Deep Learning – Tensorflow 2.0, Keras, PyTorch, Caffe
- Machine Learning – scikit-learn, Chainer, XGBoost, Caret
- NLP – Transformers, BERT, ERNIE, ELMo, SpaCy
- ML Workflow – Kubernetes, Kubvelow, MLFlow
- Data Visualization – R Shiny, Tidyverse, D3js, Neo4J
Business Training
As AI and data science become more strategically important in industry, companies must ensure that business departments are training in this growing field to ensure they take full advantage of developments. Business training courses include:
- Data Story Telling
- AI for Executives
- Machine Learning for Business
- Explainable AI
- Data and AI literacy
- Responsible AI and your company
- Data Visualization
Where is the traning conducted?
For training courses locations you have multiple choices:
Onsite team training at your office with all the advantages that brings. If you do not have suitable classroom space we can help procure classroom space close to your office. Extra charges will apply.
Offsite team training at one of our global ODSC conferences is a great alternative, especially if your budget is limited. We offer offsite training in San Francisco, Boston, New York, Dublin, London, Bangalore, and Sao Paulo. Check upcoming events here www.staging6.odsc.com
What is the cost?
Our training sessions are competitively prices and our onsite and offsite options mean we can cater to most budgets.
Cost depends on the type of the training, size of the class, and the courses selected. Please fill in our contact form and we will promptly reply.
How long are the programs?
Course duration ranges from one to five days for offsite and two to five days for onsite programs. We can extend onsite training if multiple cohorts need to be accommodated.
Can I take more than one type of course at a time?
Yes. We can tailor specific course packages based on your needs.
Are there any extra costs involved?
No. You will be aware of all the costs before the training starts. There are no additional or hidden fees.
How do i select the most suitable courses?
Since 2013, ODSC has been conduction training in this field and one of the first to do so.
A key advance to selecting us is that you can leverage our experience and insights to select the most appropriate topics for your needs. We work to understand your business goals and needs. We also provide a pre-training assessment which will help us determine team training needs.
CAN I SCHEDULE A CONSULTATION?
Yes. Please contact our Team by filling out the form here.
Is there a minimum number of attendees required for corporate training?
No, there is no minimum number.
Who are the instructors?
ODSC instructors are some of the leading experts and top practitioners in data science. They are not only highly experienced instructors but many are also core-contributors of many of the top open source data science frameworks in use. In addition many are authors of books on data science, Python, R, machine learning and deep learning. To find out more please schedule a consultation here.
Do you offer online courses?
Yes. If you would like a course to be conducted online instead of onsite this can be accommodated. Please specify this in your request on our form here.
Do you offer certification?
Yes. Your team will earn a Certificate of Completion or a Certificate of Achievement after successfully completing a post-training assessment.
Can you make a new course for my organization?
Yes. By collaborating with our instructors we can customize and create new courses specifically tailored for your organization. Please enquire by filling out our form here
Where are your Offsite training centers located?
Our offline training centers are collocated with our conference and based in Boston, San Francisco, Dublin, New York, Sao Paulo and Bengaluru.
Do you provide offsite training outside of the US?
Yes. We provide offsite training in Asia, Europe and South America.
How do you guarantee the success of the training?
ODSC has been conducting successful training sessions since 2013. We fully understand that the current way training is conducted does not always equate to a positive ROI for the companies involved. To help guarantee the success of training we provide the following:
- A pre-training consultation to ensure that your specific corporate goals are aligned with an AI path
- A pre-training assessment to evaluate your current teams current aptitude for training and allow us to ensure training session are tuned to the correct level
- An instructor with relevant qualifications in your domain & industry, along with a syllabus and content tailored for your specific needs
- A post-assessment to evaluate the progress make and essure successful alignment with training outcomes and goals.
- The AI Learning Accelerator where you will be able access video recordings of sessions and learning resources (If included in your package)
- Follow-up Recommendations for further training curriculum and skills development for the team
Where can I see the course syllabus?
We are happy to provide you with the full course syllabus. Please fill out our contact form and specify the course syllabus you are most interested in and we will reply promptly.
Conference Team Training
Each ODSC conference hosts many of the best and brightest AI and Data Science experts on the planet. Why not have your team train with the best? Hosting your team at our venue has many advantages.
Custom Team Training
Let us bring the top data science and training experts to you. We can host our classes in your offices. Alternatively, we can host your team in many locations, including Singapore, Boston, San Francisco, New York City, Bengaluru, London, Dublin & many more!