2 answers
3
Questions
2 answers
Updated
William’s Answer
Start the day with securing a job order. Get your HSE induction done for a new project. Your tools are ready. You get fully kitted with your PPE.
You may have to work in a confined space or work at height with your full blown dy harness for rope access.
Troubleshooting of faults is the order of the day. Fixing faults, upgrades or new installation might last for some period of time.
Reading of plan blueprints for the electrical drawings is a must.
It might involve extensive travel as well.
Possiblity of being a CAD Technician who prepares drawings and details from designs is their.
Thumbs up Electrician!
You may have to work in a confined space or work at height with your full blown dy harness for rope access.
Troubleshooting of faults is the order of the day. Fixing faults, upgrades or new installation might last for some period of time.
Reading of plan blueprints for the electrical drawings is a must.
It might involve extensive travel as well.
Possiblity of being a CAD Technician who prepares drawings and details from designs is their.
Thumbs up Electrician!
Updated
Sudha Rani’s Answer
Hi Jerrell,
Morning Routine: Like any other profession, your day might start with a morning routine—getting ready, having breakfast, and commuting to your workplace or setting up your remote workspace.
Reviewing and Planning: Once you're settled in, you might begin your day by reviewing your schedule, emails, and any tasks or meetings planned for the day. You might prioritize tasks based on deadlines or project requirements.
Meetings and Collaborations: Depending on your role and project requirements, you may have meetings scheduled throughout the day. These could include brainstorming sessions with colleagues, project status updates, client meetings, or discussions with stakeholders.
Coding and Development: If you're a software engineer or developer, a significant portion of your day might be spent coding and developing AI/NLP algorithms, models, or applications. This could involve writing and debugging code, testing software, and optimizing algorithms for performance.
Data Analysis and Model Training: For data scientists and machine learning engineers, a portion of the day might involve working with data—cleaning, preprocessing, analyzing, and visualizing data sets. You might also spend time training and fine-tuning machine learning models using algorithms like neural networks, decision trees, or support vector machines.
Research and Reading: Staying updated with the latest research and advancements in AI/NLP is essential in this field. You might spend time reading research papers, academic journals, or online articles to stay abreast of new techniques, algorithms, and best practices.
Problem-Solving and Troubleshooting: AI/NLP projects often come with challenges and roadblocks that require problem-solving skills. You might spend time brainstorming solutions, troubleshooting issues, or seeking help from colleagues or online communities.
Documentation and Reporting: Documenting your work, including code, methodologies, results, and findings, is crucial for collaboration, reproducibility, and knowledge sharing. You might spend time writing reports, documenting code, or updating project documentation.
Training and Learning: Continuous learning is essential in a fast-paced field like AI/NLP. You might allocate time during your day for self-study, online courses, workshops, or tutorials to enhance your skills and stay updated with new technologies and techniques.
Wrap-Up and Reflection: Towards the end of the day, you might wrap up ongoing tasks, review your progress, and plan for the next day. This could involve organizing your workspace, updating task lists, and reflecting on achievements and areas for improvement.
Morning Routine: Like any other profession, your day might start with a morning routine—getting ready, having breakfast, and commuting to your workplace or setting up your remote workspace.
Reviewing and Planning: Once you're settled in, you might begin your day by reviewing your schedule, emails, and any tasks or meetings planned for the day. You might prioritize tasks based on deadlines or project requirements.
Meetings and Collaborations: Depending on your role and project requirements, you may have meetings scheduled throughout the day. These could include brainstorming sessions with colleagues, project status updates, client meetings, or discussions with stakeholders.
Coding and Development: If you're a software engineer or developer, a significant portion of your day might be spent coding and developing AI/NLP algorithms, models, or applications. This could involve writing and debugging code, testing software, and optimizing algorithms for performance.
Data Analysis and Model Training: For data scientists and machine learning engineers, a portion of the day might involve working with data—cleaning, preprocessing, analyzing, and visualizing data sets. You might also spend time training and fine-tuning machine learning models using algorithms like neural networks, decision trees, or support vector machines.
Research and Reading: Staying updated with the latest research and advancements in AI/NLP is essential in this field. You might spend time reading research papers, academic journals, or online articles to stay abreast of new techniques, algorithms, and best practices.
Problem-Solving and Troubleshooting: AI/NLP projects often come with challenges and roadblocks that require problem-solving skills. You might spend time brainstorming solutions, troubleshooting issues, or seeking help from colleagues or online communities.
Documentation and Reporting: Documenting your work, including code, methodologies, results, and findings, is crucial for collaboration, reproducibility, and knowledge sharing. You might spend time writing reports, documenting code, or updating project documentation.
Training and Learning: Continuous learning is essential in a fast-paced field like AI/NLP. You might allocate time during your day for self-study, online courses, workshops, or tutorials to enhance your skills and stay updated with new technologies and techniques.
Wrap-Up and Reflection: Towards the end of the day, you might wrap up ongoing tasks, review your progress, and plan for the next day. This could involve organizing your workspace, updating task lists, and reflecting on achievements and areas for improvement.