Artificial Intelligence (AI) isn’t just a buzzword — it’s a game-changer, reinventing businesses, opening up new job opportunities, and changing the nature of labor in the modern world. So as you’d imagine, there’s an unprecedented demand for qualified people in this industry! Maybe you’re looking at AI as a way to future-proof yourself, but you’re not sure where to start. Regardless of whether you want to excel in your current job or make a total career pivot, let’s figure out how to start a career in AI.
Wondering how to start a career in AI?
Businesses from a variety of industries and verticals are using AI to streamline operations, create new AI-powered applications, and are incorporating AI into their products and services. A career in AI is a great choice for you if you're already excited about the prospect of utilizing cutting-edge technology and having influence in how this new technology evolves. Career choices can range from AI development, to AI integration, and even AI ethics.
So where do you start? Good news! You can start without any prior knowledge of artificial intelligence. This blog will take you through the steps you need to start a successful career in artificial intelligence.
Step 1: Evaluate your existing skill set
Before diving headfirst into the world of AI, you can determine what skills you need to develop in order to thrive in an AI job by first assessing where you currently stand. Artificial Intelligence (AI) encompasses a wide range of fields, including computer vision, robotics, data science, machine learning, and natural language processing.
You're off to a great start if you have any prior experience with programming, data analysis, or mathematics, as these skills serve as AI's cornerstone. If you don’t come from a tech background, don’t worry! Anyone willing to invest the time and effort to learn can use artificial intelligence (AI), which is also AI’s greatest feature. This blog also assumes you’ll be looking mostly into development roles, but don’t forget that AI companies need marketing, UI/UX design, accounting, etc., too!
Key skills needed for a career in AI:
- Deep learning: Acquaintance with neural networks and frameworks like TensorFlow and PyTorch.
- Programming languages: Python, R, and Java are commonly used in AI development.
- Data analysis: Understanding how to work with large datasets, clean data, and extract meaningful insights.
- Mathematics and statistics: A strong foundation of linear algebra, probability, and statistics is essential for working with algorithms.
- Machine learning: Working with the fundamentals of machine learning algorithms and knowing ways to implement them.
By comparing your current skills to these specifications, you can design a customized learning program that targets your areas of weakness.
Step 2: Find a course or courses to upskill in AI
Next step: choosing the appropriate courses to help you learn and/or upskill! From beginners to advanced developers, the internet has a whole host of online materials available for learners of all levels. There are traditional methods of learning as well, like degrees or certification programs, so be sure to check your local offerings if that’s better suited for you!
When selecting a course, think about your learning style and goals. Do you like structured learning with specific milestones, or want to learn at your own pace? Are you seeking a general introduction to AI, or are you ready to get into the nitty gritty of a specific topic such as machine learning or natural language processing?
Here are some popular online platforms where you can find high-quality AI courses:
- Skillcrush: Provides beginner-friendly courses to help you develop practical AI skills, even if you have no prior expertise. Discover the Skillcrush AI course here.
- edX: Offers a diverse selection of AI courses, including specialist degrees in machine learning and data science.
- Coursera: Features beginner to advanced level courses from prominent universities and institutes.
- Udacity: Offers nanodegree programs focused on AI, machine learning, and deep learning.
If your course doesn’t account for it, make sure to apply what you're learning with hands-on projects! This practical experience will help you construct a solid portfolio (more on that in the next step).
Step 3: Build a portfolio of AI projects
In the realm of AI, a great portfolio is your passport to a great job. Your portfolio should highlight and demonstrate your abilities to address real-world challenges with AI techniques.
Don’t be intimidated, you don’t have to assemble a full portfolio all at once! Start by working on little projects that allow you to apply the concepts covered in your courses. For example, you could design a rudimentary machine-learning model to anticipate home prices or a natural language processing chatbot.
As your confidence and skills grow, you can tackle increasingly challenging projects like creating a recommendation system, or training a deep learning model. Remember to focus on projects that are applicable to the jobs you’re going to look for, but they don’t all need to be that specific.
A few project ideas to get you started:
- Data analysis project: Analyze a dataset and display your findings with graphics and machine learning models.
- Natural language processing (NLP) project: Create a sentiment analysis program capable of classifying text as positive, negative, or neutral.
- Computer vision project: Develop an image recognition model capable of classifying items in photographs.
- AI-powered web app: Create a web app that leverages AI to make personalized suggestions or automate processes.
Document your projects thoroughly, including the issue statement, approach, tools and technology employed, and outcomes. This documentation will not only help you keep track of your work, but will also provide useful context for future employers reviewing your portfolio.
Step 4: Network with AI professionals and enthusiasts
Yup, you can’t escape it – networking is an essential part of every successful career, and AI is no different. Building relationships with AI experts and enthusiasts can lead to career opportunities, mentorship, and partnerships.
Star with accessing online communities and forums where AI experts share expertise, analyze trends, and provide advice. LinkedIn, GitHub, and Reddit are excellent sites for networking with like-minded people.
Consider attending AI conferences, seminars, and meetups (both virtual and in-person) to grow your network. These events allow you to learn from industry experts, stay up to date on the newest developments, and meet possible employers or collaborators. (Editor’s note: there are loads of free options here, too!)
Lastly, don’t be scared to (respectfully) contact professionals whose work you admire or look-up-to! Sending a thoughtful message showing your interest in their work and seeking for help or mentorship can be a nice boost for them and a networking opportunity for you.
Step 5: Start applying for AI jobs
It’s time. You’re now ready to apply for AI jobs. Like most other gigs, when applying for AI positions, make sure your CV/resume and cover letter highlight your relevant abilities, projects, and experience, especially since you just put in so much work to get ready! Employers are typically also interested in your ability to solve real-world problems with AI, so stress those skills too!
Here are some job titles to start narrowing down your search:
- AI consultant: Assists organizations integrate AI into their operations and offers guidance on AI strategy and implementation.
- Machine learning engineer: Works on the design and implementation of machine learning models and algorithms.
- AI researcher: Performs research to advance the field of AI and develop new algorithms and techniques.
- Data scientist: Evaluates and interprets complex data to aid organizations make cognizant decisions.
- AI product manager: Supervises the development and deployment of AI products, guaranteeing they meet business goals and user needs.
PSST – the PowerToFly Job Board is a great resource for finding AI-related positions that match your skills and interests!
Your AI career journey starts now
Remember, the path to an AI job is a marathon, not a sprint. Continuous learning and staying current on the newest advances in AI are critical for remaining relevant and succeeding in your job. Take the first step today, and you may end up as the next AI expert to shape the future.
Check out our other blog posts for more insights on how AI can help advance your career:
