Nick Kolakowski’s Post

Much like technology itself, the fundamental skills that tech managers need to excel on the job are continuing to evolve at a rapid pace. For instance, as more organizations eliminate managerial and principal engineering roles to create flatter structures, the remaining managers are expected to serve as player-coaches, noted Josh Bob, career coach for tech managers and founder of Career Vision Coaching. “Under the circumstances, having the ability to understand the code on a deep level and the soft skills to coach and motivate team members to work harder and reach higher levels of achievement is a big plus,” Bob said. From the technical to the tactical to the social, here are the skills and competencies that have become indispensable to ascend into tech management, along with some ways to acquire them. #management #AI #techskills

Our latest “Tech Connects” #podcast guest is Laura Baldwin, who’s the president of O’Reilly Media. If you’ve worked in tech, you’re well aware of O’Reilly’s training offerings, which include a massive online learning platform. I wanted to talk with Laura because of her insight into how companies are upskilling their workers for AI, the ethical implications of AI, and much more. Let’s listen in! #AI #techskills #techjobs

A fascinating look at the future of #AI in the context of #techjobs and the #techindustry!

Whether you’re interested in sharing your knowledge and opinions on the latest technical tools and processes, guiding newbies toward new and exciting careers, or building your professional brand and cachet, becoming a tech influencer could be the way to go. These days, social media, podcasts, blogs and online videos give outgoing communicators the opportunity to share content and slowly build a community of loyal followers. In fact, its possible to turn your passion into a lucrative side hustle or full-time career by devoting the necessary time and effort. Would you like to be more influential? If so, here’s a look at the steps to becoming a tech influencer. #influencer #techjobs #techskills

Machine Learning (ML) is a type of artificial intelligence (AI) whereby software will analyze data, and from there make predictions based on that data. As new data comes in, the predictions are compared against results, which are added to the data. Over time, the app will find patterns, and make more accurate predictions… not unlike the way humans will learn over time. The concept of machine learning has been around for decades. Companies that deal in huge amounts of data, such as Amazon, have long been on the forefront. Amazon in particular has developed algorithms that, for example, can predict what items a customer would like to purchase. But as a profitable profession, it’s just getting started. Here's a breakdown of how a machine learning engineer (or ML engineer) develops software that makes use of machine learning algorithms. #machinelearning #techjobs #jobskills

The specter of tight budgets and layoffs looms large for many companies. In this climate, convincing your manager to invest in new technology, especially something as nascent as AI, can feel like a daunting task. However, if you think AI is absolutely essential for your tech stack and workflows, you can rely on a handful of techniques to sell the concept to whoever in your organization holds the purse strings. Let's be honest, AI (particularly generative AI chatbots such as ChatGPT and Google’s Gemini) is still evolving. While its potential is undeniable, concrete ROI (Return on Investment) data remains scarce in many circumstances. Managers are rightfully cautious about unproven solutions, especially when budgets are stretched thin. Here’s the thing: rather than steer away from that uncertainty, acknowledge it. Start by framing your proposal as a strategic investment in the future. #AI #generativeAI #ROI

Deep learning, a field within AI, is a type of machine learning whereby software uses deep layers of neural networks to find patterns in complex data. It’s a highly specialized but burgeoning field—and an attractive one for tech professionals who want to participate in the growing AI revolution. One important part of deep learning is what’s known as “feature learning,” whereby the software is able to determine what aspects of complex data are more important than others, and then use that knowledge to recognize patterns. With traditional machine learning applied to facial recognition, software might measure the ratios of the different distances between facial features such as eyes, noses, ears, and mouths. But with deep learning, the software isn’t programmed specifically to make such measurements; instead, the deep learning application might be given many different photos of the same person, and then start to discover on its own what similarities to focus on. As you can imagine, deep learning is a highly advanced profession and requires a great deal of study. Let’s look at how you can specialize in deep learning. #deeplearning #artificialintelligence #jobskills

No tech professional operates in a vacuum: on a daily basis, you need to communicate frequently with non-technical colleagues in marketing, sales, the C-suite, and other departments. And while you may have no problem discussing the nuances of APIs and algorithms, those colleagues may have precious little idea what you’re talking about when it comes to tech. How can you bridge this “communication gap” and ensure that your messages about deliverables, resources, and projects truly resonates with them? #communication #softskills #techskills