Predictive Analytics Training in Oslo

This instructor-led, live training in Oslo (online or onsite) is aimed at intermediate-level developers who wish to build AI-powered applications using predictive analytics and generative models.

By the end of this training, participants will be able to:

• Understand the fundamentals of predictive AI and generative models.
• Utilize AI-powered tools for predictive coding, forecasting, and automation.
• Implement LLMs (Large Language Models) and transformers for text and code generation.
• Apply time-series forecasting and AI-based recommendations.
• Develop and fine-tune AI models for real-world applications.
• Evaluate ethical considerations and best practices in AI deployment.

This instructor-led, live training in Oslo (online or onsite) is aimed at intermediate-level data professionals who wish to apply machine learning techniques to data-driven business problems, including sales forecasting and predictive modeling using neural networks.

By the end of this training, participants will be able to:

• Grasp the fundamental concepts and types of machine learning.
• Apply essential algorithms for classification, regression, clustering, and association analysis.
• Conduct exploratory data analysis and prepare data using Python.
• Utilize neural networks for nonlinear modeling tasks.
• Implement predictive analytics for business forecasting, including sales data.
• Assess and optimize model performance using visual and statistical techniques.

This instructor-led live training, delivered in Oslo (online or onsite), is tailored for beginner-level IT professionals who want to master the fundamentals of Predictive AI.

By the end of this training, participants will be able to:

• Grasp the fundamental principles of Predictive AI and its practical applications.
• Gather, clean, and prepare data for predictive analysis.
• Analyze and visualize data to reveal key insights.
• Construct basic statistical models to generate predictions.
• Assess the effectiveness of predictive models.
• Implement Predictive AI concepts in real-world situations.

This instructor-led, live training in Oslo (online or onsite) is aimed at intermediate-level DevOps professionals who wish to integrate predictive AI into their DevOps practices.

By the end of this training, participants will be able to:

• Implement predictive analytics models to forecast and solve challenges in the DevOps pipeline.
• Utilize AI-driven tools for enhanced monitoring and operations.
• Apply machine learning techniques to improve software delivery workflows.
• Design AI strategies for proactive issue resolution and optimization.
• Navigate the ethical considerations of using AI in DevOps.

In this instructor-led live training Oslo, participants will cultivate the mindset required to approach Big Data technologies, assess their impact on existing processes and policies, and implement these technologies to identify and prevent criminal activity. By analyzing case studies from law enforcement organizations worldwide, participants will gain insights into adoption strategies, challenges, and outcomes.

By the end of this training, participants will be able to:

• Combine Big Data technology with traditional data gathering processes to piece together a story during an investigation.
• Implement industrial big data storage and processing solutions for data analysis.
• Prepare a proposal for the adoption of the most adequate tools and processes for enabling a data-driven approach to criminal investigation.

Audience

Are you looking to make sense of the data at your disposal or analyze unstructured data sources available online (such as Twitter, LinkedIn, etc.)? This course is tailored for you.

It is primarily designed for decision-makers and professionals who need to determine which data is valuable to collect and analyze.

It is not intended for individuals focused on configuring solutions, although they will gain value from the broader perspective offered.

Delivery Mode

During the course, delegates will be presented with working examples primarily utilizing open-source technologies.

Short lectures will be followed by presentations and simple exercises led by participants.

Content and Software used

All software utilized is updated for each course iteration, ensuring the use of the latest possible versions.

The curriculum covers the entire process from obtaining, formatting, processing, and analyzing data, to explaining how to automate decision-making processes through machine learning.

This instructor-led live training in Oslo (online or onsite) is designed for data scientists and analysts who wish to automate, evaluate, and manage predictive models using DataRobot’s machine learning capabilities.

By the end of this training, participants will be able to:

• Import datasets into DataRobot to analyze, evaluate, and perform quality checks.
• Construct and train models to identify key variables and achieve prediction objectives.
• Interpret models to generate valuable insights that support business decision-making.
• Monitor and manage models to ensure optimized prediction performance.

R is an open-source, free programming language designed for statistical computing, data analysis, and graphical visualization. It is increasingly utilized by managers and data analysts within both corporate and academic sectors. R offers a vast array of packages for data mining.

Predictive analytics involves leveraging data analytics to forecast future outcomes. This approach combines data with techniques from data mining, statistics, and machine learning to construct predictive models that anticipate upcoming events.

In this instructor-led live training, participants will acquire the skills to use Matlab for building predictive models and applying them to large-scale datasets to predict future occurrences based on historical data.

Upon completion of this training, participants will be able to:

• Develop predictive models to analyze patterns in historical and transactional data
• Utilize predictive modeling to identify potential risks and opportunities
• Construct mathematical models that capture significant trends
• Leverage data from devices and business systems to minimize waste, save time, or reduce costs

Audience

• Developers
• Engineers
• Domain experts

Format of the course

• Combination of lectures, discussions, exercises, and extensive hands-on practice

R is a free, open-source programming language designed for statistical computing, data analysis, and visualisation. It is increasingly adopted by managers and data analysts within both corporate environments and academic institutions. R offers an extensive range of packages dedicated to data mining.

RapidMiner is an open-source data science platform designed for rapid application prototyping and development. It features an integrated environment supporting data preparation, machine learning, deep learning, text mining, and predictive analytics.

In this instructor-led live training, participants will learn to utilize RapidMiner Studio for data preparation, machine learning, and the deployment of predictive models.

Upon completion of this training, participants will be able to:

• Install and configure RapidMiner
• Prepare and visualize data using RapidMiner
• Validate machine learning models
• Combine data sources and build predictive models
• Implement predictive analytics within business processes
• Troubleshoot and optimize RapidMiner

Audience

• Data scientists
• Engineers
• Developers

Course Format

• A blend of lectures, discussions, exercises, and extensive hands-on practice

Note

• To request customized training for this course, please contact us to make arrangements.

This instructor-led live training, available either online or on-site, targets analysts, researchers, and professionals at the beginner to intermediate levels who aim to leverage SPSS for data preparation, statistical analysis, and predictive modeling.