Matlab for Predictive Analytics Training Course

In this instructor-led, live training in US, participants will gain a comprehensive understanding of Big Data technologies, assess their impact on existing processes and policies, and implement these technologies for the purpose of identifying criminal activity and preventing crime. Case studies from law enforcement agencies around the world will be examined to provide insights into their adoption approaches, challenges, and outcomes.

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

• Integrate Big Data technology with traditional data gathering methods to construct a coherent narrative during an investigation.
• Implement scalable big data storage and processing solutions for effective data analysis.
• Develop a proposal for the adoption of the most suitable tools and processes to enable a data-driven approach to criminal investigations, tailored specifically for government use.

Audience

This course is designed for individuals who need to interpret and analyze the data they have access to, as well as those interested in analyzing unstructured data from online sources such as Twitter and LinkedIn. It is primarily intended for decision-makers and professionals responsible for determining which data is valuable to collect and analyze.

While it is not specifically tailored for individuals configuring the solutions, these participants will still gain a comprehensive understanding of the overall process.

Delivery Mode

The course delivery includes practical demonstrations using primarily open-source technologies. Short lectures will be followed by presentations and hands-on exercises to ensure active participation.

Content and Software Used

All software utilized in the course is regularly updated to include the latest versions available, ensuring that participants receive the most current training. The curriculum covers the entire data management process, from acquisition and formatting to processing and analysis, with a focus on automating decision-making processes through machine learning techniques for government use.

This instructor-led, live training (online or onsite) is aimed at data scientists and data analysts who wish to automate, evaluate, and manage predictive models using DataRobot's machine learning capabilities for government applications. By the end of this training, participants will be able to: - Load datasets in DataRobin to analyze, assess, and quality check data. - Build and train models to identify key variables and meet prediction targets. - Interpret models to derive actionable insights that support informed decision-making. - Monitor and manage models to ensure ongoing optimization and performance.

• Recognize the significance of ethics in AI development and deployment for government.

• Acquire skills to identify and mitigate ethical risks associated with AI systems.

• Gain an understanding of regulatory and compliance requirements relevant to AI.

• Develop strategies for fostering an ethical AI culture within government organizations.

Format of the Course

• Interactive lectures and discussions.
• Extensive exercises and practice sessions.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

This instructor-led, live training (online or onsite) is designed for intermediate-level developers who aim to build AI-powered applications using predictive analytics and generative models. By the end of this training, participants will be able to: - Understand the foundational principles of predictive AI and generative models. - Utilize AI-driven tools for predictive coding, forecasting, and automation. - Implement Large Language Models (LLMs) and transformers for text and code generation. - Apply time-series forecasting and AI-based recommendations in their projects. - Develop and fine-tune AI models for practical applications. - Evaluate ethical considerations and best practices in the deployment of AI solutions for government.

This instructor-led, live training in [location] (online or onsite) is designed for beginner-level IT professionals who wish to understand the fundamentals of Predictive AI for government. By the end of this training, participants will be able to: - Comprehend the core concepts of Predictive AI and their applications. - Gather, clean, and preprocess data for predictive analysis. - Explore and visualize data to uncover valuable insights. - Construct basic statistical models to generate predictions. - Assess the performance of predictive models. - Apply Predictive AI concepts to real-world scenarios within government operations.

R is an open-source programming language designed for statistical computing, data analysis, and graphical representation. It is increasingly utilized by managers and data analysts in both the corporate sector and academic institutions. R offers a broad range of packages that facilitate data mining, making it a valuable tool for government and other public sector applications.

MATLAB, a numerical computing environment and programming language developed by MathWorks, is widely utilized for government and academic research. It provides robust tools and functionalities that support complex data analysis and algorithm development, aligning well with the technical requirements for government projects.

This two-day course provides a comprehensive introduction to the MATLAB® technical computing environment for government. The course is intended for beginner users and those looking for a review. No prior programming experience or knowledge of MATLAB is assumed. Themes of data analysis, visualization, modeling, and programming are explored throughout the course, with an emphasis on aligning these skills with public sector workflows and governance.

This instructor-led, live training in [location] (online or onsite) is designed for intermediate-level data professionals who seek 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: - Understand the fundamental concepts and types of machine learning. - Apply key algorithms for classification, regression, clustering, and association analysis. - Conduct exploratory data analysis and data preparation using Python. - Utilize neural networks for nonlinear modeling tasks. - Implement predictive analytics for business forecasting, including sales data. - Evaluate and optimize model performance using visual and statistical techniques. This training is tailored to enhance the skills of data professionals in the public sector, ensuring they are well-equipped to address complex challenges and improve decision-making processes for government.

This instructor-led, live training (online or onsite) is designed for intermediate-level DevOps professionals who aim to integrate predictive artificial intelligence into their DevOps practices. By the end of this training, participants will be able to: - Implement predictive analytics models to forecast and address challenges in the DevOps pipeline. - Utilize AI-driven tools to enhance monitoring and operations. - Apply machine learning techniques to improve software delivery workflows for government. - Design AI strategies for proactive issue resolution and optimization. - Navigate the ethical considerations of using AI in DevOps.

R is an open-source programming language designed for statistical computing, data analysis, and graphics. It is increasingly utilized by managers and data analysts in both the corporate and academic sectors. R offers a comprehensive array of packages for data mining, making it a valuable tool for government and other public sector workflows.

RapidMiner is an open-source data science software platform designed for rapid application prototyping and development. It offers an integrated environment for data preparation, machine learning, deep learning, text mining, and predictive analytics. In this instructor-led, live training, participants will learn how to use RapidMiner Studio for data preparation, machine learning, and the deployment of predictive models. By the end 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 create predictive models - Integrate predictive analytics into business processes - Troubleshoot and optimize RapidMiner for government applications **Audience** - Data scientists - Engineers - Developers **Format of the Course** - Part lecture, part discussion, exercises, and extensive hands-on practice **Note** - To request a customized training for this course tailored to specific needs, please contact us to arrange.

This course provides comprehensive material on MATLAB as a robust simulation tool for communications. The objective of this course is to introduce MATLAB not only as a general programming language but also to highlight its extensive capabilities as a simulation tool. The examples provided are designed to illustrate the course content through practical, real-world problems, ensuring that participants gain a deep understanding of how to apply these tools effectively for government and industry applications.

This instructor-led, live training (available online or on-site) is designed for government analysts, researchers, and professionals at the beginner to intermediate level. Participants will learn to utilize SPSS for data preparation, statistical analysis, and predictive modeling, enhancing their capabilities in data-driven decision-making for government operations.