Machine Learning’s Post

Today's Data Engineering tools are broken. I remember the time when the rise of web development frameworks started, I think never reached these levels. Well, fortunately, we can use this as an opportunity to architect solutions that truly generates value. At first, we just need turn back to the roots, starting to acknowledge that AI/ML is not Data Engineering nor Deep Learning Framework, we can filter already some noise around. The business requirements will tell you most of the Data Processing needs for the particular use case and you can start working in an architectural draft containing data sources, specially orchestration followed of analytics tools, governance, policies etc. Be aware of the commitments, risk assessment, matrix costs are your best friends when dealing with project management. Small victories will unlock confidence in your problem solving road map.

Another thing that was clear to me from reviewing the data is that AI benefits complex projects. The larger your data sets for research and analysis, the more AI-powered tech can make it easy for you to sift through the data. APM’s research says that IT and Technology projects are most likely to see a benefit from AI but I think over time we’ll also see legal project management and construction seeing benefits due to the huge amounts of data that can be used in those projects. I think that the biggest barrier to making use of this advancement is having clean data. I would suggest that any project teams looking to use the analytical power of data models and LLMs need to schedule time on the plan for data cleansing and preparation. Read more here: https://lnkd.in/eDq9G2k4

The Importance of Authentic Metadata in AECO Project Management In #AECO, embracing good data hygiene isn't just about organization—it's about foresight. A recent getconcert.com article highlights the crucial role of authentic metadata in enhancing analytics and leveraging AI/ML technologies. Accurate and well-maintained data empowers us to anticipate and address potential issues before they escalate. By prioritizing data integrity, we're not only streamlining our processes but also unlocking the potential for advanced, predictive problem-solving. Let's commit to meticulous data management, setting the stage for smarter, more efficient project outcomes in the AECO sector. https://loom.ly/eulgZNs #AI #architecture #design

Sometimes there is simply no substitute for learning things the hard way. At the end of the linked post, I describe a hands-on exercise that I've used to teach people the practical value of simplicity, decomposition, scope management, and a clear definition of "done" when planning a project or program. Remember: to succeed you must first *visualize* the path to your goal! https://lnkd.in/ewpnCX8b

Wrapping up one of the most pivotal years in technology, we examine the role of artificial intelligence in project management: what's available today and what is likely to become reality in the coming months. https://lnkd.in/duJyTnWB Among the available tools is the transparency and interpretation of complex data, which we've implemented in ITM Platform through the AI-generated Reports feature. This converts underlying data (earned value, workflow, financials, time estimates, issues, risks, etc.) into human-readable reports.

AI Tools for Project Management: Streamline Your Workflow!😎 👉AI project management tools enhance efficiency and collaboration by automating tasks and providing real-time data analysis. These tools assist teams in meeting project objectives and deadlines with greater accuracy. ➡️ https://lnkd.in/gqnqsqSK 🔎 𝗛𝗔𝗦𝗛𝗧𝗔𝗚S #aitools #bestaitools #aivariance #aitoolsforProjectManagement #blogs

Approaching AI Project Planning: Crafting Your Blueprint for Success ✏️ Planning an AI project is like charting a course for an exciting voyage into uncharted waters. It involves not just choosing the destination but also preparing the right crew, mapping out the route, & readying the ship for potential storms and pirates. Here’s how to plot your course with precision and foresight, ensuring a successful journey from conception to deployment. 1. Define Objectives & Scope Start by clearly defining what you want to achieve with your AI project. Like setting coordinates for your journey, this step involves pinpointing the exact outcomes you expect from the AI implementation. Are you aiming to improve efficiency, enhance customer satisfaction, or drive innovation? Establishing clear goals at the outset helps to guide the project's direction and measure its success. 2. Assess Data Readiness Data is the wind that powers your AI sail. Assess the quality, availability, & relevance of the data you plan to use. Is it sufficient to train your models effectively? Are there gaps that need to be filled? Sometimes, you might need to set sail to gather more data before you can embark on the full journey. Ensure your data is clean, organized, and aligned with your project goals. 3. Choose the Right Tools & Technology Selecting the appropriate tools and technology for your AI project is like choosing the right ship for your voyage. Consider the complexity of the tasks at hand, the scalability required, and the compatibility with existing systems. Whether it’s machine learning frameworks like TensorFlow or cloud services like AWS, the right technology stack can make or break your project. 4. Map Out the Project Timeline Every voyage has its milestones and checkpoints. Develop a detailed project timeline that includes key phases such as data preparation, model training, testing, and deployment. Set realistic timelines for each phase, taking into account potential delays and adjustments. This roadmap will help keep the project on track. 5. Plan for Risks & Mitigation The sea is unpredictable, and so is the AI landscape. Identify potential risks to your project, such as data privacy issues, changes in technology standards, or unexpected operational hurdles. Develop strategies to mitigate these risks, such as data anonymization techniques, keeping abreast of technology trends, and having contingency plans in place. 6. Iterate & Optimize No voyage is perfect on the first try, and neither is an AI project. Be prepared to iterate on your models and strategies based on feedback and performance data. Continuous improvement is key to refining your AI solutions and achieving the best results. Conclusion With careful planning and execution, you can navigate the complexities of your AI initiative, much like a seasoned captain steering through the high seas, ready to explore the vast potentials of AI. Bon Voyage! 🚢 #ProjectPlanning #TechLeadership #ArtificialIntelligence

📢 Announcement: Data Pirates Agency Begins Testing Tecna AI We are excited to share some thrilling news with our community! Data Pirates Agency has been selected to test Tecna, a groundbreaking AI platform designed to revolutionize project management. Thanks to Robin Svensson's recent call for teams to participate in this innovative project, we have the unique opportunity to be among the first to explore and implement Tecna's capabilities. As leaders in innovation and efficiency, we are always on the lookout for tools that can enhance our operations. Tecna promises to do just that with its advanced features aimed at optimizing workflow, improving collaboration, and driving project success. Key Benefits of Tecna: - Enhanced Efficiency: Tecna’s AI-driven tools streamline project management tasks, allowing us to focus more on creativity and strategy. - Seamless Collaboration: With Tecna, team communication and coordination are set to become more fluid and effective. - Innovative Solutions: By being early adopters, we have the unique opportunity to influence the development of Tecna, tailoring it to our specific needs. Our Involvement: As part of this exclusive testing phase, Data Pirates Agency will be among the first to explore and implement Tecna's capabilities. We are eager to see how this cutting-edge technology can elevate our projects and deliver even greater value to our clients. We’re proud to lead the charge in adopting this innovative AI platform and are committed to providing valuable feedback to help shape Tecna’s future. Stay tuned for more updates as we embark on this exciting journey. Together, we’re setting sail towards a new horizon in project management! Anchors aweigh! Rami S. Jaber  Chief Engineer   Data Pirates Agency Follow us for more updates.

Another professional win for generative AI: I track all of my time. Sometimes I want to export my time tracking from my project management software to a spreadsheet in order to perform additional calculations. The spreadsheet export of the time tracking column puts it in a HH:MM:SS format, which doesn't work for calculations. I figured there had to be a formula I could use to convert the HH:MM:SS format to a total minute format. Here comes the fun part: I used ExcelBrew to ask for a formula. I simply described the formula I wanted: "Convert a time sum formatted as 00:04:12 to a format that can be totaled." In less than a second it gave me the exact formula I needed! =HOUR(A1)*60 MINUTE(A1) SECOND(A1)/60 It even has a copy button that you can click and then paste into the spreadsheet. ⭐️ BONUS: It works with Excel and Google Sheets. https://lnkd.in/gbx4F_xR

Decomposing complex tasks into simpler subtasks makes them more manageable and ensures clearer, more accurate AI responses. This strategy is particularly useful in project management, skill acquisition, and software development, providing structured guidance for achieving detailed and high-quality results.