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TRAINING PROGRAM

Our extensive in-house knowledge and high levels of expertise allow us to provide the support you need to achieve complete confidence in the subject area you are seeking training.  Training is available online and in person.

e-Learning

An extensive portfolio of off-the-shelf e-Learning courses bundled by topic (e.g. Professional Development; EDI), providing immediate & cost-effective training solutions.

Custom Training

TC content creators help design, produce and deliver custom-designed training, including virtual instructor-led training (VILT) sessions, eLearning modules and video elements.

LMS & Managed Services

Clients have access to a Learning Management System (LMS) platform to serve as the foundation for sustainable L&D while reducing investment requirements.

Onsite Customer Training

Our trained staff can conduct training sessions for individuals & groups at the client’s location to save time & money.

Training Courses

Course Overview: This course is designed to enhance participants’ skills in communicating technical information within laboratory settings. From documentation to effective collaboration, participants will learn the nuances of conveying complex scientific concepts clearly and concisely.

Module 1: Introduction to Technical Communication in Laboratories

  • Importance of Clear Communication in Scientific Research
  • Overview of Technical Writing in Laboratory Environments
  • Addressing Specific Communication Challenges in Laboratories

Module 2: Documenting Laboratory Procedures and Protocols

  • Structuring Clear and Precise Standard Operating Procedures (SOPs)
  • Importance of Detail and Clarity in Laboratory Manuals
  • Incorporating Visual Aids for Enhanced Understanding

Module 3: Writing Effective Lab Reports

  • Components of a Comprehensive Lab Report
  • Data Presentation and Analysis
  • Interpreting and Communicating Results

Module 4: Collaborative Communication in Scientific Teams

  • Effective Team Communication Strategies
  • Collaborative Document Editing and Version Control
  • Facilitating Productive Laboratory Meetings

Module 5: Technical Communication Tools in Laboratories

  • Utilizing Laboratory Information Management Systems (LIMS)
  • Documenting in Electronic Lab Notebooks (ELNs)
  • Integration of Communication Tools for Seamless Collaboration

Module 6: Writing for Various Audiences

  • Adapting Communication Style for Peers, Superiors, and External Stakeholders
  • Crafting Communicative Abstracts for Publications
  • Writing Grant Proposals and Research Funding Applications

Module 7: Visual Communication in Laboratories

  • Design Principles for Scientific Posters
  • Creating Clear and Informative Graphs and Figures
  • Utilizing Infographics for Data Representation

Module 8: Ethical Considerations in Laboratory Communication

  • Proper Attribution and Citation in Scientific Writing
  • Addressing Authorship and Acknowledgment
  • Maintaining Integrity in Laboratory Communication

Practical Assignments: Participants will engage in practical assignments, including drafting SOPs, lab reports, and collaborative documents. They will also create visual aids and presentations for effective communication.

Assessment: Evaluation will be based on the quality of written assignments, collaborative projects, and a final presentation showcasing effective technical communication skills.

Duration: The course is designed for 2 weeks, with 15 hours of instruction per week.

Target Audience:

  • Laboratory Technicians
  • Researchers and Scientists
  • Professionals involved in Scientific Communication

Certification: Upon successful completion, participants will receive a certificate of achievement, recognizing their proficiency in Laboratory Technical Communication.

Course Overview: This advanced course is designed to provide participants with a deep understanding of how Artificial Intelligence is transforming laboratory processes. From data analysis to predictive modeling, participants will explore practical applications of AI, enhancing efficiency and innovation in scientific research.

Module 1: Introduction to AI in Laboratories

  • Understanding Artificial Intelligence
  • Overview of Machine Learning and Deep Learning
  • Importance of AI in Laboratory Settings

Module 2: Data Management and Preprocessing for AI

  • Data Collection and Sources
  • Data Cleaning and Transformation
  • Feature Engineering for Improved Model Performance

Module 3: Machine Learning Applications in Laboratories

  • Predictive Modeling for Experimentation
  • Classification and Regression Techniques
  • Model Evaluation and Validation

Module 4: Deep Learning in Scientific Research

  • Neural Networks and Architecture
  • Applications in Image Analysis and Pattern Recognition
  • Case Studies of Deep Learning Successes in Laboratories

Module 5: Natural Language Processing (NLP) for Research

  • Overview of NLP in Laboratory Documentation
  • Text Mining and Analysis Techniques
  • Extracting Insights from Scientific Literature

Module 6: Laboratory Automation with AI

  • Robotic Process Automation (RPA)
  • AI-Driven Laboratory Equipment
  • Integration of AI in Experiment Design and Execution

Module 7: Ethical Considerations and Challenges

  • Ensuring Ethical Use of AI in Laboratories
  • Addressing Bias and Fairness in AI Algorithms
  • Challenges and Limitations of AI in Scientific Research

Module 8: Future Trends and Innovations

  • Emerging Technologies in AI
  • Industry-Specific Innovations in Laboratory AI
  • Staying Updated in the Dynamic AI Landscape

Practical Projects: Participants will engage in hands-on projects, applying AI techniques to laboratory scenarios. This includes data analysis, model building, and implementing AI solutions for specific research challenges.

Assessment: Evaluation will be based on project submissions, quizzes, and a final presentation where participants showcase their understanding and application of AI concepts in laboratory settings.

Duration: The course is designed for 1 weeks, with 40 hours of instruction per week.

Target Audience:

  • Laboratory Researchers and Scientists
  • Professionals in Scientific Data Analysis
  • Those seeking to integrate AI into laboratory processes

Certification: Upon successful completion, participants will receive a certificate of achievement, recognizing their proficiency in the Application of Artificial Intelligence in Laboratory Settings.

Course Overview: This course is designed to instill a culture of safety in laboratory settings. Participants will learn essential safety protocols, best practices, and preventative measures to create a secure and compliant working environment.

Module 1: Introduction to Laboratory Safety

  • Importance of Lab Safety
  • Regulatory Frameworks and Standards
  • Responsibilities of Laboratory Personnel

Module 2: Hazard Identification and Risk Assessment

  • Identifying Potential Hazards in the Lab
  • Conducting Risk Assessments
  • Strategies for Mitigating Risks

Module 3: Personal Protective Equipment (PPE)

  • Selection and Proper Use of PPE
  • Maintenance and Inspection
  • Emergency Situations and PPE Usage

Module 4: Chemical Safety and Handling

  • Safe Chemical Storage and Labeling
  • Understanding Material Safety Data Sheets (MSDS)
  • Protocols for Chemical Spill Response

Module 5: Biological Safety Protocols

  • Handling Biological Agents Safely
  • Biosafety Levels and Containment Practices
  • Waste Disposal Procedures for Biological Materials

Module 6: Equipment Safety and Maintenance

  • Proper Handling of Laboratory Equipment
  • Regular Maintenance and Calibration
  • Emergency Shutdown Procedures

Module 7: Emergency Response and Evacuation Procedures

  • Developing and Communicating Emergency Plans
  • Fire Safety Protocols
  • Evacuation Drills and Procedures

Module 8: Best Practices for Laboratory Ergonomics

  • Designing Ergonomic Workstations
  • Preventing Laboratory-Related Injuries
  • Promoting Overall Well-being in the Lab

Practical Exercises: Participants will engage in hands-on exercises, including emergency response simulations, PPE fitting sessions, and equipment safety checks.

Assessment: Evaluation will be based on participation in practical exercises, quizzes, and a final assessment that tests participants’ knowledge of lab safety protocols.

Duration: The course is designed for 1 weeks.

Target Audience:

  • Laboratory Technicians and Researchers
  • Students in Scientific Disciplines
  • Professionals involved in Lab Management

Certification: Upon successful completion, participants will receive a certificate of achievement, recognizing their proficiency in Lab Safety Protocols and Best Practices.

Course Overview: This course aims to equip participants with the knowledge and skills to integrate sustainable practices into laboratory operations. From energy efficiency to waste reduction, participants will explore strategies to minimize environmental impact while maintaining high standards of scientific research.

Module 1: Introduction to Sustainable Laboratory Practices

  • Understanding Sustainability in the Laboratory Context
  • Importance of Sustainable Operations
  • Aligning Sustainable Practices with Scientific Goals

Module 2: Energy Efficiency in Laboratories

  • Assessing Energy Consumption in Laboratories
  • Implementing Energy-Saving Technologies
  • Strategies for Efficient Equipment Use

Module 3: Waste Reduction and Management

  • Minimizing Single-Use Plastics and Materials
  • Implementing Recycling Programs
  • Sustainable Approaches to Laboratory Waste Disposal

Module 4: Green Chemistry and Eco-Friendly Materials

  • Introduction to Green Chemistry Principles
  • Substituting Hazardous Chemicals with Eco-Friendly Alternatives
  • Sustainable Procurement Practices

Module 5: Water Conservation Strategies

  • Assessing Water Usage in Laboratories
  • Implementing Water-Saving Technologies
  • Best Practices for Water Management

Module 6: Laboratory Design for Sustainability

  • Sustainable Lab Construction and Renovation
  • Optimizing Lab Layout for Energy Efficiency
  • Green Building Certifications and Standards

Module 7: Biodiversity Conservation in Laboratory Settings

  • Incorporating Green Spaces and Living Laboratories
  • Promoting Biodiversity within Laboratory Facilities
  • Integrating Sustainable Landscaping Practices

Module 8: Metrics and Reporting for Sustainable Laboratories

  • Establishing Key Performance Indicators (KPIs) for Sustainability
  • Monitoring and Reporting Sustainable Practices
  • Communicating Achievements and Progress

Practical Exercises: Participants will engage in practical exercises, including energy audits, waste reduction plans, and sustainable procurement assessments.

Assessment: Evaluation will be based on practical exercises, quizzes, and a final project where participants develop a sustainable practices implementation plan for a hypothetical laboratory.

Duration: The course is designed for 1 weeks, with 2 hours of instruction per Day.

Target Audience:

  • Laboratory Managers and Supervisors
  • Researchers and Scientists
  • Environmental and Sustainability Professionals

Certification: Upon successful completion, participants will receive a certificate of achievement, recognizing their proficiency in Sustainable Practices in Laboratory Operations.

Course Overview: This course is designed to provide participants with a comprehensive understanding of quality assurance principles and compliance requirements within laboratory settings. Participants will learn how to maintain high standards, adhere to regulations, and ensure the reliability of laboratory results.

Module 1: Introduction to Quality Assurance in Laboratories

  • Importance of Quality Assurance
  • Principles of Quality Management
  • Link between Quality Assurance and Laboratory Excellence

Module 2: Regulatory Frameworks and Standards

  • Overview of National and International Standards
  • Compliance with Regulatory Bodies
  • Key Standards in Laboratory Operations

Module 3: Documentation and Record Keeping

  • Establishing Effective Documentation Systems
  • Good Documentation Practices (GDP)
  • Digital Record Keeping and Laboratory Information Management Systems (LIMS)

Module 4: Validation and Verification Processes

  • Importance of Validation in Laboratory Methods
  • Conducting Verification Studies
  • Equipment and Method Validation Protocols

Module 5: Internal Audits and Quality Control

  • Implementing Internal Audit Programs
  • Designing Effective Quality Control Systems
  • Continuous Improvement through Internal Audits

Module 6: Corrective and Preventive Actions (CAPA)

  • Identifying Non-Conformities and Deviations
  • Root Cause Analysis
  • Developing Robust CAPA Plans

Module 7: Risk Management in Laboratory Operations

  • Identifying and Assessing Risks
  • Risk Mitigation Strategies
  • Integrating Risk Management into Laboratory Processes

Module 8: External Audits and Accreditation

  • Preparing for External Audits
  • Achieving and Maintaining Laboratory Accreditation
  • Benefits of Accreditation in Laboratory Operations

Practical Exercises: Participants will engage in practical exercises, including developing documentation templates, conducting internal audits, and creating risk management plans.

Assessment: Evaluation will be based on participation in practical exercises, quizzes, and a final project where participants apply quality assurance principles to a specific laboratory scenario.

Duration: The course is designed for 1 weeks, with 2 hours of instruction per Day.

Target Audience:

  • Laboratory Managers and Supervisors
  • Quality Assurance Personnel
  • Professionals involved in Laboratory Compliance

Certification: Upon successful completion, participants will receive a certificate of achievement, recognizing their proficiency in Quality Assurance and Compliance in Laboratories.

Course Overview: This course is designed to equip participants with the knowledge and skills to leverage digital technologies for efficient data management and information handling within laboratory settings. Participants will explore strategies for implementing digital tools, enhancing collaboration, and ensuring data integrity.

Module 1: Introduction to Digitalization in Laboratories

  • Understanding Digital Transformation
  • Importance of Digitalization in Laboratory Operations
  • Benefits and Challenges of Adopting Digital Technologies

Module 2: Laboratory Information Management Systems (LIMS)

  • Overview of LIMS and their Functions
  • Implementation and Integration of LIMS
  • Optimizing Workflows with LIMS

Module 3: Electronic Lab Notebooks (ELNs)

  • Advantages of ELNs in Data Recording
  • Transitioning from Paper to Digital Notebooks
  • Ensuring Data Security and Integrity with ELNs

Module 4: Digital Data Capture and Analysis

  • Implementing Automated Data Capture
  • Data Analysis Techniques and Tools
  • Visualization of Laboratory Data

Module 5: Cloud-Based Solutions for Lab Data

  • Benefits and Risks of Cloud-Based Storage
  • Collaborative Work in Cloud Environments
  • Ensuring Data Security in the Cloud

Module 6: Data Governance and Compliance

  • Establishing Data Governance Policies
  • Ensuring Compliance with Regulatory Standards
  • Data Integrity and Traceability

Module 7: Integration of Digital Tools in Laboratory Equipment

  • Connecting Instruments for Seamless Data Transfer
  • IoT (Internet of Things) in Laboratories
  • Automation and Robotics for Data Generation

Module 8: Cybersecurity in Laboratory Digitalization

  • Understanding Cybersecurity Risks
  • Best Practices for Securing Laboratory Data
  • Training Personnel on Cybersecurity Awareness

Practical Exercises: Participants will engage in practical exercises, including setting up a digital laboratory system, utilizing LIMS, and implementing cybersecurity measures.

Assessment: Evaluation will be based on participation in practical exercises, quizzes, and a final project where participants propose a digitalization plan for a hypothetical laboratory.

Duration: The course is designed for 1 weeks, with 2 hours of instruction per Day.

Target Audience:

  • Laboratory Managers and Technicians
  • Researchers and Scientists
  • Professionals involved in Lab Data Management

Certification: Upon successful completion, participants will receive a certificate of achievement, recognizing their proficiency in Digitalization of Lab Data and Information Management.

The “TCP/IP Communication” course is designed to delve into the intricacies of the Transmission Control Protocol/Internet Protocol (TCP/IP), a fundamental suite of protocols governing communication on the internet. This course provides participants with a comprehensive understanding of how data is transmitted, routed, and received across networks using the TCP/IP protocol stack.

Key components of the course include the layered architecture of TCP/IP, addressing schemes, and the protocols that facilitate reliable and efficient data transfer. Participants will gain insights into networking concepts such as IP addressing, subnetting, and the role of protocols like TCP and UDP in ensuring seamless communication between devices.

Through practical exercises and real-world applications, participants will develop the skills needed to configure and troubleshoot TCP/IP networks. This course is ideal for individuals pursuing careers in network administration, system engineering, or anyone seeking an in-depth understanding of the protocols underpinning modern internet communication.

Course Overview: This course is designed to explore the latest advancements and innovations in laboratory automation. Participants will gain insights into cutting-edge technologies and strategies transforming laboratory processes for increased efficiency, accuracy, and productivity.

Module 1: Introduction to Laboratory Automation

  • Evolution of Laboratory Automation
  • Key Drivers for Automation Adoption
  • Benefits and Challenges of Automation in Laboratories

Module 2: Robotic Process Automation (RPA)

  • Overview of RPA in Laboratory Workflows
  • Applications in Sample Handling and Processing
  • Integrating Robotics for Repetitive Tasks

Module 3: High-Throughput Screening (HTS) Technologies

  • Principles and Applications of HTS
  • Automated Assay Development
  • Accelerating Drug Discovery through HTS

Module 4: Laboratory Information Management Systems (LIMS) Integration

  • Enhancing Data Management with LIMS
  • Connecting Instruments and Systems for Seamless Operation
  • Real-time Monitoring and Reporting

Module 5: Artificial Intelligence (AI) and Machine Learning in Automation

  • Applications of AI and Machine Learning in Laboratory Settings
  • Predictive Analytics for Experimentation
  • Optimizing Workflows through Intelligent Automation

Module 6: Lab-on-a-Chip Technologies

  • Miniaturization of Laboratory Processes
  • Applications in Diagnostics and Analytical Chemistry
  • Microfluidics and Lab-on-a-Chip Platforms

Module 7: 3D Printing in Laboratory Automation

  • Customization of Lab Equipment
  • Rapid Prototyping for Lab Tools
  • Advances in 3D Printing Materials

Module 8: Future Trends and Innovations

  • Emerging Technologies in Laboratory Automation
  • Industry-Specific Innovations
  • Staying Ahead in the Dynamic Landscape

Practical Exercises: Participants will engage in hands-on exercises, including setting up automated workflows, utilizing robotic systems, and exploring AI applications in laboratory scenarios.

Assessment: Evaluation will be based on participation in practical exercises, quizzes, and a final project where participants propose an automation strategy for a hypothetical laboratory.

Duration: The course is designed for 1 weeks, with 2 hours of instruction per Day.

Target Audience:

  • Laboratory Managers and Technicians
  • Researchers and Scientists
  • Professionals involved in Lab Automation and Instrumentation

Certification: Upon successful completion, participants will receive a certificate of achievement, recognizing their proficiency in Advancements in Laboratory Automation.

Embark on a voyage through the latest breakthroughs in laboratory instrumentation with our “Innovations in Laboratory Equipment” course. Uncover the most advanced analytical tools, imaging devices, and diagnostic equipment reshaping the landscape of scientific exploration. Delve into real-world case studies and applications, gaining a comprehensive understanding of how these innovations propel research and experimentation to new heights. Perfect for professionals and enthusiasts eager to stay at the forefront of laboratory technology.

Course Overview: This course is designed to guide participants in implementing best practices to enhance the reproducibility of research in laboratory settings. Participants will learn methodologies, protocols, and strategies to ensure that research findings can be accurately and reliably reproduced.

Module 1: Introduction to Research Reproducibility

  • Understanding the Importance of Reproducibility
  • Challenges in Achieving Reproducible Results
  • Impact of Reproducibility on Scientific Integrity

Module 2: Transparent Research Design and Methodology

  • Documenting and Sharing Research Protocols
  • Establishing Clear Experimental Design
  • Pre-registration of Research Studies

Module 3: Data Management and Transparency

  • Best Practices in Data Collection and Storage
  • Transparent Reporting of Data
  • Utilizing Open Data Platforms

Module 4: Statistical Analysis and Reporting

  • Transparent Statistical Methods
  • Handling Statistical Significance and P-Values
  • Promoting Transparent Reporting of Statistical Analyses

Module 5: Quality Control and Assurance

  • Implementing Quality Control Measures in Experiments
  • Ensuring Data Integrity
  • Documenting Quality Assurance Protocols

Module 6: Reproducible Data Visualization and Presentation

  • Best Practices in Graphical Representations
  • Utilizing Reproducible Tools for Data Visualization
  • Transparent Data Presentation in Publications

Module 7: Collaborative Research Practices

  • Encouraging Collaboration and Reproducibility
  • Reproducibility in Multi-Laboratory Studies
  • Strategies for Effective Data Sharing

Module 8: Ethical Considerations in Research Reproducibility

  • Addressing Authorship and Contributorship
  • Dealing with Irreproducible Results
  • Responsible Conduct of Research

Practical Exercises: Participants will engage in practical exercises, including documenting protocols, conducting transparent data analysis, and collaborating on reproducible research projects.

Assessment: Evaluation will be based on participation in practical exercises, quizzes, and a final project where participants develop a reproducibility plan for a hypothetical research study.

Duration: The course is designed for 1 weeks, with 2 hours of instruction per Day.

Target Audience:

  • Researchers and Scientists
  • Laboratory Managers and Technicians
  • Professionals involved in Scientific Research

Certification: Upon successful completion, participants will receive a certificate of achievement, recognizing their proficiency in Laboratory Best Practices for Research Reproducibility.

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