AI (Artificial Intelligence) is changing the way industries operate – from manufacturing robot automation to smart assistants on our smartphones. If you’re not familiar with AI, you may be wondering how to get started.
This blog is here to provide a guide to understand how you can break into AI courses online, regardless of your level of technical knowledge, and create your career around one of the most sought-after skill sets of the future. Whether you’re a student, you just want to change careers, or you’re casually interested in AI, there will be a clear path for you to follow when you are learning AI courses online.
Online education is on the rise and you don’t need to attend an expensive university or have a technical degree, you just need to have the right mindset, resources that structure learning, and a desire to practice what you learn, one step at a time!
Why AI? Why Now?
AI isn’t just for scientists or programmers. All businesses need AI practitioners for:
- Predictive analytics
- Chatbots and automation
- Personalized marketing
- Risk assessment and management
- Smart healthcare and diagnostics
According to a recent study by Humans of Globe, the global AI market is expected to reach $1.8 trillion by 2030, and we are already experiencing a shortage of skilled workers. This means it’s the perfect time to get started, especially through flexible and affordable AI courses online.
Step 1: Learn the Basics of AI Courses Online
Before diving into AI, you first need to understand what AI is. You don’t have to become an expert overnight; you simply need to understand the main concepts. Start with:
- What is Artificial Intelligence?
- What is the difference between Artificial Intelligence, Machine Learning, and Deep Learning?
- Good examples in the real world- self-driving cars, recommendations via Netflix, voice assistants
Recommended Courses:
Step 2: Master Basic Python
Python is the primary programming language for AI programs. Fortunately for you, Python is one of the easiest languages to learn.
- Your focus right now is:
- Writing cleaner code
- Using libraries, like NumPy or Pandas
- Working through beginner problems on HackerRank or LeetCode and so on.
Recommended Courses:
Step 3: Get familiar with MATH
To understand how AI works, you are going to need some math, which you will be learning the basics. The only focus is
- Linear Algebra (for deep learning)
- Probability / Statistics (for ML Models)
- Calculus (optional, nice to know for deeper understanding)
Step 4: Take Beginner Enabling Artificial Intelligence Courses
Now you have the basics under your belt, you can learn how AI works in practice. Search for your course with criteria of:
- Structured modules
- Real world projects
- Certificate, this can be beneficial when looking for work!
Recommended courses:
Artificial Intelligence- Bootcamp
Step 5: Build Actual Projects to Get Hands-on Practice
In the long run, theory is important, but presumably, employers care about your ability to solve practical problems.
- Consider simple projects:
- Spam detection
- Sentiment analysis of twitter as an example
- Predicting housing prices
- A chatbot using NLP
Once you complete a project, put it on GitHub to show your skills to an employer. Many AI courses online include capstone projects that are ideal for your portfolio.
Step 6: Join Online Communities
It’s easier to learn AI when you join a community.
Try:
- Reddit: r/MachineLearning
- Kaggle forums
- AI niche Discord servers
- LinkedIn Groups like AI in Industry or Women in AI
Ask questions, participate in challenges, and network with mentors.
Step 7: Create a Personal AI Portfolio
Create a portfolio that includes:
- The projects you put together with complete documentation
- Your Github profile
- Blog posts or short write-up on LinkedIn about what it means to you
- Any relevant certification
Your portfolio speaks louder than your resume, especially since you are entering a new field.
Step 8: Apply for Internships or Entry Level Role
Once you have an AI portfolio with some personal projects, you can begin applying for any opportunity. This is when you start looking for:
- Freelance work
- Internships with start-ups
- Research assistant
- Data annotation/machine learning model testing
Even small roles can lead to big opportunities and breakthroughs.
Challenges
The journey of learning AI can be thrilling, but it is not without some challenges:
-
Information Overload: Moving slowly and using visual supports
-
Math Anxiety – Sticking with one course/topic at a time
-
Imposter Syndrome – Reminding that everyone started somewhere
Outlook on Future AI Careers
AI is changing quickly and so are jobs of the future. Potential career opportunities you could explore include:
- AI Product Manager
- Machine Learning Engineer
- Natural Language Processing (NLP) Specialist
- AI Ethics Researcher
FAQ’s
Q1. Do I need a degree in computer science to become an AI professional?
No – many AI professionals did not even have a formal education in technology and instead learned AI by using a variety of learning options, including online courses and videos, and practicing their skills.
Q3. Is AI only for coders?
No – many AI professionals did not even have a formal education in technology and instead learned AI by using a variety of learning options, including AI courses online and videos, and practicing their skills.
Wrapping Up
Starting your career in AI can be intimidating, but you can build a solid foundation by taking it one step at a time. The digital world needs many more AI-literate professionals—it’s easier than ever to get started with the variety of AI courses online available today.
Are you ready to future-proof your career?
Take part in the AI Bootcamps from Big Data Trunk to learn from industry experts, build completed projects for your portfolio, and earn certification. Our experiential training programs will walk you from student, to professional, to career switcher, and more with an excellent curriculum that prepares you for opportunities in AI.
Visit www.BigDataTrunk.com and enroll today to start your journey into AI!
