Predictive Analytics Training in Kuala Lumpur

This instructor-led, live training in Kuala Lumpur (online or onsite) is designed for intermediate-level developers who aim to build AI-powered applications using predictive analytics and generative models.

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

• Grasp the fundamentals of predictive AI and generative models.
• Leverage AI-powered 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-driven recommendation systems.
• Develop and fine-tune AI models for real-world applications.
• Assess ethical considerations and best practices in AI deployment.

This instructor-led, live session (online or onsite) is designed for intermediate data professionals aiming to apply machine learning techniques to business problems, including sales forecasting and neural network-based predictive modeling.

By the conclusion of this training, attendees will be able to:

• Comprehend core machine learning concepts and types.
• Apply key algorithms for classification, regression, clustering, and association analysis.
• Perform exploratory data analysis and data preparation using Python.
• Use 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 instructor-led, live training in Kuala Lumpur (online or onsite) is aimed at beginner-level IT professionals who wish to grasp the fundamentals of Predictive AI.

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

• Understand the core concepts of Predictive AI and its applications.
• Collect, clean, and preprocess data for predictive analysis.
• Explore and visualize data to uncover insights.
• Build basic statistical models to make predictions.
• Evaluate the performance of predictive models.
• Apply Predictive AI concepts to real-world scenarios.

This instructor-led live training in Kuala Lumpur (online or onsite) targets intermediate-level DevOps professionals keen on incorporating predictive AI into their workflows.

By the conclusion 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 for improved monitoring and operations.
• Apply machine learning techniques to enhance software delivery workflows.
• Design AI strategies for proactive issue resolution and optimization.
• Navigate the ethical considerations associated with using AI in DevOps.

In this instructor-led live training in Kuala Lumpur, participants will develop the mindset required to approach Big Data technologies, assess their impact on existing processes and policies, and implement these technologies to identify criminal activity and prevent crime. Case studies from law enforcement organisations around the world will be examined to gain insights into their adoption approaches, challenges, and results.

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.

Target Audience

This course is designed for individuals who aim to interpret accessible data or analyse unstructured data from online platforms such as Twitter and LinkedIn.

It primarily targets decision-makers and professionals responsible for determining which data sets are valuable to collect and analyse.

While those configuring the solutions are not the primary focus, they will also benefit from gaining a broader perspective.

Delivery Mode

Participants will be shown practical examples of predominantly open-source technologies throughout the course.

The sessions combine short lectures with presentations and straightforward exercises conducted by the delegates.

Content and Software Used

All software utilized is updated for every course run, ensuring the latest versions are employed.

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

This instructor-led live training in Kuala Lumpur (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:

• Load datasets in DataRobot to analyze, assess, and quality check data.
• Build and train models to identify important variables and meet prediction targets.
• Interpret models to create valuable insights that are useful in making business decisions.
• Monitor and manage models to maintain an optimized prediction performance.

R is a free, open-source programming language designed for statistical computing, data analysis, and graphical visualization. Its adoption is expanding rapidly among corporate managers, data analysts, and academic researchers. R boasts an extensive ecosystem of packages tailored for data mining and analytical tasks.

Predictive analytics involves leveraging data analytics to forecast future outcomes. By combining data with techniques from data mining, statistics, and machine learning, this process establishes predictive models capable of anticipating future events.

In this instructor-led live training, participants will learn how to utilize Matlab to construct predictive models and apply them to large sample datasets to forecast future events based on the data.

Upon completing this training, participants will be able to:

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

Audience

• Developers
• Engineers
• Domain experts

Format of the course

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

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

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

Through this instructor-led live training, participants will gain practical skills in utilizing RapidMiner Studio for data preparation, machine learning, and the deployment of predictive models.

By the conclusion of this training, participants will be equipped to:

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

Audience

• Data scientists
• Engineers
• Developers

Format of the Course

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

Note

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

This instructor-led live training (available online or onsite) targets analysts, researchers, and professionals at beginner to intermediate levels who aim to leverage SPSS for data preparation, statistical analysis, and predictive modelling.