Machine Learning Training
What if Machine Learning training is your key to remaining competitive?
Need help finding the right learning solutions? Email Us: info@developintelligence.com
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Get your team started on a custom learning journey today!
Our Boulder, CO-based learning experts are ready to help!
- Apache Kafka Courses
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Expert practitioners facilitate our Machine Learning training
Instructor-Led | Role-Based | Tailored To Your Project
Today, Machine Learning training isn’t optional. Organizations are leveraging Machine Learning to gain a competitive advantage. A wide range of applications—from self-driving cars to e-commerce sites—rely on ML to look at past data in an effort to predict the future.
The goals? To serve customers better, drive efficiency and outflank competitors.
Stay ahead of the Machine Learning curve with help from DevelopIntelligence.
Our Machine Learning Training Team
Our experts are well-known industry practitioners. They have hands-on, in-the-trenches experience with the specific technologies they teach. When not training for DevelopIntelligence, they regularly author technical papers on the evolution of tools and languages in the field, speak at industry conferences, and contribute to open-source projects.
Get More Information
Chat with one of our tech experts to create a custom on-site or online training program.
Boost your competitiveness with Machine Learning training from DevelopIntelligence.
Available Courses:
Learn how to use the high-throughput, distributed, publish-subscribe messaging system Apache Kafka.
Learn to utilize Kafka Streams and identify where Kafka can be further incorporated into practice.
Learn to use Apache Kafka as a distributed messaging system.
Real-Time Ingestion & Processing Using Kafka & Spark
Learn the knowledge and skills needed to utilize Data Ingestion and Processing using Kafka and Spark Streaming.
Learn how to use Spark internals for working with NoSQL databases as well debugging and troubleshooting.
Learn how to use Apache Spark as an alternative to traditional MapReduce processing.
Introduction to Apache Spark in Production
Learn about the architecture and internals of Spark, a fast and general engine for big data processing with built-in modules for streaming, SQL, machine learning, and graph processing.
Learn about and build end-to-end SML pipelines for gaining actionable insights.
Learn best practices and techniques to optimize Spark Core and Spark SQL code.
Artificial Intelligence for Product Managers
Learn the practical skills to plan, implement and manage an AI program.
Introduction to Artificial Intelligence
Learn the foundational and practical knowledge of artificial intelligence.
Introduction to Artificial Intelligence and Machine Learning in Azure
Learn how to implement AI and ML techniques on Azure.
Machine Learning and Natural Language Processing
Learn to implement ML techniques for Natural Language comprehension, sentiment analysis, topic discovery, etc.
Promote an in-depth understanding of the challenges and opportunities of machine learning.
Administering SQL Server in Azure
Learn about how the SQL Server database administrator (DBA) role changes when administering SQL Server in Azure with running SQL Server on Azure Virtual Machines or using Azure SQL Database.
Learn to build end-to-end data applications using Microsoft Azure and understand which tools are best suited to certain problems and use-cases.
Learn how to analyze Azure costs and employ governance best practices to manage and optimize costs in an Azure account. Compare/contrast value and demand and evaluate decisions.
Learn how to deploy, configure and manage Azure using Chef.
Azure for System Administrators
Learn how to configure, maintain and monitor Azure Virtual Machines and Virtual Networks.
Learn how to build, deploy, and maintain applications in Azure Cloud.
Data Services Architecture with Azure
This course provides a detailed overview of the different data services in Microsoft Azure.
Developing Scalable Applications on Azure
Learn how to develop a globally distributed application using Azure and serverless concepts
Implementing Microsoft Azure Infrastructure Solutions Certification
Learn how to pass the "Implementing Microsoft Azure Infrastructure Solutions" certification exam.
Intermediate Azure for Architects
This course covers everything a cloud solutions architect needs to know to plan and design solutions for the Microsoft Azure cloud platform. This course focuses on how to modernize existing workloads and make them cloud-able in true sense.
Introduction to Artificial Intelligence and Machine Learning in Azure
Learn how to implement AI and ML techniques on Azure.
Introduction to Azure for Architects
This course introduces you to everything a cloud solutions architect needs to know to plan and design solutions for Microsoft Azure cloud platform.
Introduction to Azure for Developers
Learn how to build, deploy, secure, scale, monitor and maintain applications in Azure Cloud.
Introduction to Azure for Managers
Learn how to plan and manage cloud team resources more effectively.
Introduction to the Azure Stack and VM Managers
Learn how to deploy and manage Azure in private data centers.
Microsoft Azure Certification Boot Camp
Learn the information necessary to pass the Developing Microsoft Azure Solutions Certification Exam.
SQL Server 2019 Performance Improvements
Learn about performance related features and improvements specific to SQL Server 2019 and the latest version of Azure SQL Database.
SQL Server Performance Optimization and Troubleshooting
Learn to address common real-life performance problems both at the server and T-SQL code level. Learn about troubleshooting approaches, techniques, features and tools with SQL Server 2019 and Azure SQL Database.
Working with Big Data on Azure
Learn how to use Big Data technologies on the Azure cloud.
Building Chatbots Using Google Dialogflow
Learn how to build a Chatbot on Google Cloud and deploy it standalone as well as on Facebook Messenger.
Implementing AI using IBM Watson Chatbots
Promote an in-depth understanding of Chatbots and how to implement them using IBM Cloud.
Developers and non-developers looking to leverage Microsoft Power Platform in their businesses.
Advanced Programming of High-Performance GPU Architectures
Learn about advanced programming techniques for OpenCL programming on Intel, AMD, and Nvidia architectures.
High-Performance GPU Architectures
Learn the approach and practices to using GPU architectures for high performance computing.
Introduction to High-Performance GPU Architectures
Learn about CUDA programming, profiling, and debugging techniques required to develop general purpose software applications for GPU hardware.
Introduction to SageMaker for Data Analysts
Learn how to choose the right questions to ask and how to answer them with ML.
Learn the knowledge and use cases for software engineers to transition to Machine Learning for Search.
Learn to understand, design, implement and assess the impact of deep learning techniques for a diverse range of visual recognition tasks.
Deep Learning with TensorFlow and Keras
Learn Deep Learning concepts and popular tools.
Working with Deep Reinforcement Learning
Learn about deep reinforcement learning, what it is, how it works, and how you can apply it to real-world problems.
Building Chatbots Using Google Dialogflow
Learn how to build a Chatbot on Google Cloud and deploy it standalone as well as on Facebook Messenger.
Google Cloud for Data Analysts
Learn how to perform insightful and responsive data analysis at scale and delight the consumers of the analysis with effective data visualizations.
Google Cloud for Data Engineers
Learn to build systems on Google Cloud to store and process batch or streaming data.
Google Cloud for Data Scientists
Learn how to create and deploy high-performance data science and machine learning systems on Google Cloud for regression and classification use cases leveraging both structured and unstructured datasets.
Learn to create and deploy software on Google Cloud to have secure and stable applications.
Learn about Google Cloud and its technical capabilities in the areas of IT infrastructure, operations, Big Data, and Machine Learning.
Intermediate Google Cloud For Data Analysts
Learn how to analyze large scale, distributed, and real-time datasets with MapReduce and Apache Beam based capabilities of Google Cloud and practice identification and analysis of effective data features for predictive analytics with BigQuery ML and TensorFlow.
Intermediate Google Cloud for Data Engineers
Learn how to use data engineering on Google Cloud to build specialized data pipelines for large scale streaming data analytics, machine learning, and recommendation systems.
Intermediate Google Cloud For Data Scientists
Learn how to implement statistical and machine learning models using TensorFlow, for example for recommendation engines, and how to improve their performance based on the students’ understanding of underlying mathematical principles.
Intermediate Google Cloud for Developers
Learn how to utilize advanced processes and practices for the platform to improve function and security.
Learn to use Google's BigQuery to explore and gain insights from large datasets.
Introduction to Cloud Computing
Learn about the different cloud providers and what they offer.
Introduction to the Google App Engine
Learn how to use Java to set up a project with the Google App Engine and integrate it with other Google Cloud services.
Moving to a Hybrid Cloud for Managers Adding Google Cloud
Learn how to develop a platform-based infrastructure using Google Cloud.
Learn the fundamental skills needed to manage large scale infrastructure with SaltStack on major cloud providers (AWS, Google Cloud and Azure).
Artificial Intelligence for Product Managers
Learn the practical skills to plan, implement and manage an AI program.
Machine Learning and Natural Language Processing
Learn to implement ML techniques for Natural Language comprehension, sentiment analysis, topic discovery, etc.
Natural Language Processing with Python
Promote an in-depth understanding on how to use Natural Language Processing in your Python applications.
Learn advanced techniques for managing data and tuning models.
Learn how to become an expert at creating high-throughput, multithreaded, network oriented programs written in Python.
Applied Data Science & Machine Learning
Learn intermediate data analysis techniques and how programming languages can be used to further analyze data.
Building a Recommendation Engine Using Python
Learn to design, implement and evaluate various recommendation engines.
Data Analysis with SQL and Python
Provide students with the advanced SQL skills needed for effective data analysis.
Promote an intermediate understanding of Python and increase developer skills and techniques.
Introduction to Data Science & Machine Learning
Learn how data can be gathered to improve the overall needs of the business.
Introduction to Graphics Processing
Learn a working knowledge of graphics processing practices within Machine Learning using CUDA, PyCuda, OpenCL, Vulkan, and Tensorflow.
Introduction to Machine Learning
Learn various Machine Learning algorithms to evaluate and productize models.
Learn how to create basic programs using Python.
Learn how to develop simple programs using fundamental Python concepts.
Introduction to Python for DevOps/Scripting
Provide DevOps engineers the Python skills they need for scripting, automation, and to enhance productivity.
Learn both R and Python programming languages by providing comparisons and recommendations between both.
Learn how to use MongoDB with Python.
Natural Language Processing with Python
Promote an in-depth understanding on how to use Natural Language Processing in your Python applications.
Learn how to use Python to explore and analyze data, run basic regression models, visualize data, and apply some basic machine learning models to data.
Learn how to implement statistical and machine learning models using PyTorch and how to improve their performance based on an understanding of underlying mathematical principles.
Software Engineering in Python
Learn software engineering techniques using Python.
Learn how to implement statistical and machine learning models using PyTorch and how to improve their performance based on an understanding of underlying mathematical principles.
Learn how to leverage R to perform data analytics and graph best practices.
Learn both R and Python programming languages by providing comparisons and recommendations between both.
Learn how to use R as a tool to perform data science, machine learning or statistics on large data sets.
Introduction to SageMaker for Data Analysts
Learn how to choose the right questions to ask and how to answer them with ML.
Learn how to improve analytical ability and the ability to provide data insights.
Learn how to identify the right context for analysis, perform the analysis and tell a story to drive action.
Learn advanced Tableau knowledge and skills.
Learn the fundamentals of Tableau.
Deep Learning with TensorFlow and Keras
Learn Deep Learning concepts and popular tools.
Google Cloud for Data Engineers
Learn to build systems on Google Cloud to store and process batch or streaming data.
Google Cloud for Data Scientists
Learn how to create and deploy high-performance data science and machine learning systems on Google Cloud for regression and classification use cases leveraging both structured and unstructured datasets.
Intermediate Google Cloud for Data Engineers
Learn how to use data engineering on Google Cloud to build specialized data pipelines for large scale streaming data analytics, machine learning, and recommendation systems.
Intermediate Google Cloud For Data Scientists
Learn how to implement statistical and machine learning models using TensorFlow, for example for recommendation engines, and how to improve their performance based on the students’ understanding of underlying mathematical principles.
Machine Learning and Natural Language Processing
Learn to implement ML techniques for Natural Language comprehension, sentiment analysis, topic discovery, etc.
