When tech changes, the skills an organization needs also change. As a technologist, what skills should you prioritize learning to build or boost your tech career? As a leader, how can you help your teams develop these skills through effective upskilling programs?
Here’s the breakdown. (Spoiler alert: It’s not all about generative AI.)
What the next big technology trends mean for your tech skills
Learn these hard and soft skills for a successful career in tech.
Data and data engineering skills
Data has always been important, but the prevalence of AI has made it even more of a priority. Develop data analytics skills to unlock the full business value of your data. This includes the ability to:
Clean, transform, and analyze data
Recognize when data is flawed, biased, missing, or incomplete
Select a machine learning algorithm
Train and evaluate models
Visualize data
In terms of specific technologies, SQL and noSQL database skills are still in high demand as well as big data analytics technologies like Apache Spark, Databricks, and Tableau. It’s also important to get familiar with libraries used for machine learning, like TensorFlow and PyTorch.
Build data analytics skills with hands-on practice.
Programming skills
When it comes to programming, it's no surprise Python came out on top as one of the most in-demand languages for 2024. I always think of Python as the programming language of the cloud—it's versatile, easy to use, and suitable for use cases like web development, automation, data science, and AI and machine learning. Beyond Python, object-oriented languages like Java, JavaScript, and C# are still going strong.
Cybersecurity, cloud, and AI skills
70% of organizations run more than half their infrastructure in the cloud. And many use a multicloud strategy or multiple cloud providers. Securing everything is a major concern for many organizations.
That’s why security, and cloud security specifically, came out as a top skill to develop. Get hands-on experience with the top three cloud providers—AWS, Azure, and GCP—to understand how these systems work. Understanding the shared responsibility model will also give you a real-world perspective on cloud security.
And while AI will accelerate existing security threats and introduce new risks, you can also use AI and machine learning to help protect your environment. For example, Amazon Guard Duty is a threat detection service that uses machine learning to identify malicious or unusual activity in your AWS account.
Build your AI skills.
FinOps skills and cost optimization
Successful companies are focused on cost control—protecting their return on investments or ROI. As the ultimate guide to doing more with less, FinOps is an excellent skill to add to your arsenal.
Using FinOps strategies can help you optimize your organization’s cloud and AI investments. Architect cloud infrastructure using cloud cost optimization strategies and FinOps best practices.
When it comes to AI adoption, many organizations are still understanding the cost implications of the decisions they make around training models and how much data they use to train them. For example, the type of model you select will impact your tech investment ROI.
Build FinOps foundations.
Soft skills like creativity, critical thinking, and communication
In a world where many of us might be concerned about being replaced by an overly enthusiastic AI, human-centric and soft skills have never been more relevant. This includes:
Complex problem-solving
Creativity
Critical thinking
Empathy
Communication
Leadership
Stakeholder management
Negotiation
Flexibility and adaptability
Learn why soft skills matter (more than coding) for technical roles.
How to build employee training programs for trending tech skills
As a leader, what can you do to help technologists develop these in-demand skills and drive your organization forward?
Align business goals and customer outcomes
The secret that all successful companies have in common? A strategic plan focused on customer outcomes. Define business goals and the problems you want to solve using technology.
This becomes the North Star for your technical and upskilling decisions. For instance, it will drive which cloud provider or service to use for a particular project and what skills your teams need to use it.
Create a strategic plan for upskilling
Organizations that want to stay on top also need a comprehensive plan for upskilling. If you happen to be a leader, or even a mentor or senior engineer, make it your mission to identify the future superstars within your organization.
Think about who in your organization is your next data analysis expert, Python genius, or security specialist. We often see that little spark of potential in our team members before they know it themselves. Help the people around you create professional development objectives and participate in mentorship programs.
Think about introducing protected learning time and incentivize your people to develop the expertise you need within your organization.
Develop personalized learning paths
Organizations struggle to keep learners engaged with upskilling programs. Personalized learning experiences with custom learning paths and bite-sized online courses surface the right content at the right time. Upskilling augmented by chatbots and AI assistants can also help technologists seek out targeted learning based on their existing skills and career goals.
Get tips on creating personalized learning plans for tech teams.
Make the most of tech skill development
From data analytics to personalized learning, keeping up with in-demand tech skills and trends will help you and your org build and deliver faster.
Develop the tech skills orgs need. Start a free trial of Pluralsight Skills for you or your team.
The above is the detailed content of IT skills you (and your tech teams) need to develop at work. For more information, please follow other related articles on the PHP Chinese website!

TomergelistsinPython,youcanusethe operator,extendmethod,listcomprehension,oritertools.chain,eachwithspecificadvantages:1)The operatorissimplebutlessefficientforlargelists;2)extendismemory-efficientbutmodifiestheoriginallist;3)listcomprehensionoffersf

In Python 3, two lists can be connected through a variety of methods: 1) Use operator, which is suitable for small lists, but is inefficient for large lists; 2) Use extend method, which is suitable for large lists, with high memory efficiency, but will modify the original list; 3) Use * operator, which is suitable for merging multiple lists, without modifying the original list; 4) Use itertools.chain, which is suitable for large data sets, with high memory efficiency.

Using the join() method is the most efficient way to connect strings from lists in Python. 1) Use the join() method to be efficient and easy to read. 2) The cycle uses operators inefficiently for large lists. 3) The combination of list comprehension and join() is suitable for scenarios that require conversion. 4) The reduce() method is suitable for other types of reductions, but is inefficient for string concatenation. The complete sentence ends.

PythonexecutionistheprocessoftransformingPythoncodeintoexecutableinstructions.1)Theinterpreterreadsthecode,convertingitintobytecode,whichthePythonVirtualMachine(PVM)executes.2)TheGlobalInterpreterLock(GIL)managesthreadexecution,potentiallylimitingmul

Key features of Python include: 1. The syntax is concise and easy to understand, suitable for beginners; 2. Dynamic type system, improving development speed; 3. Rich standard library, supporting multiple tasks; 4. Strong community and ecosystem, providing extensive support; 5. Interpretation, suitable for scripting and rapid prototyping; 6. Multi-paradigm support, suitable for various programming styles.

Python is an interpreted language, but it also includes the compilation process. 1) Python code is first compiled into bytecode. 2) Bytecode is interpreted and executed by Python virtual machine. 3) This hybrid mechanism makes Python both flexible and efficient, but not as fast as a fully compiled language.

Useaforloopwheniteratingoverasequenceorforaspecificnumberoftimes;useawhileloopwhencontinuinguntilaconditionismet.Forloopsareidealforknownsequences,whilewhileloopssuitsituationswithundeterminediterations.

Pythonloopscanleadtoerrorslikeinfiniteloops,modifyinglistsduringiteration,off-by-oneerrors,zero-indexingissues,andnestedloopinefficiencies.Toavoidthese:1)Use'i


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

VSCode Windows 64-bit Download
A free and powerful IDE editor launched by Microsoft

Notepad++7.3.1
Easy-to-use and free code editor

SAP NetWeaver Server Adapter for Eclipse
Integrate Eclipse with SAP NetWeaver application server.

SublimeText3 Mac version
God-level code editing software (SublimeText3)

ZendStudio 13.5.1 Mac
Powerful PHP integrated development environment
