From chatbots helping you online with work and assignments to self-driving cars hitting the road, AI is everywhere. However, with the growing presence of AI, there’s a considerable amount of confusion, especially among students, surrounding it.
Myths about AI are stopping students from exploring this exciting field. Whether it’s thinking you need to be a tech genius or fearing AI will steal jobs, these myths create unnecessary roadblocks. In this blog, we’ll bust the most common AI myths and show you why diving into AI could be one of the best decisions you make for your future. Let’s get the facts right!
Confused about starting your AI journey? Learn from the facts — not the myths!
Top 10 AI Myths Students Believe — Busted
1. AI Is Only for Science Students
Many believe that only science students can pursue AI, but that’s not true! In reality, students from all streams (Commerce, Arts, or Humanities) can dive into AI with the right foundational training.
Although having a background in subjects like mathematics helps but it’s not a requirement to get started. For example, a student from a non-science background can take introductory courses in programming, machine learning, and data science, and then apply for AI-focused degrees like a B.Sc in IT (AI). With the right mindset and resources, AI is open to anyone, regardless of their academic background.
Yes, commerce & arts students can do AI. Apply now to get started.
2. You Must Know Coding Before Learning AI
The truth is, most beginner-friendly AI courses, like a B.Sc in IT (AI), teach coding from scratch, so you don’t need to be afraid. These programs usually begin with the basics, like Python or logic building, which are essential for AI and data science.
Each semester will help you get a hold of AI. For example, learning how to code is one of the first things covered in the semester 1 curriculum, wherein you’ll only be introduced to programming fundamentals and problem solving. With the right guidance and consistent practice, anyone can learn to code, whether you’re starting from zero or refreshing your skills.
Don’t worry if you’ve never coded. We’ll teach you step-by-step. Check out our beginner-friendly curriculum.
3. AI Requires Advanced Math
You don’t need to be a math genius to work in AI. While math is involved, it’s not about mastering complex formulas from day one. Most AI concepts are built on basic algebra, logic, and problem-solving skills that anyone can learn with practice.
Real-world examples, like how recommendation systems suggest products or how AI can recognize faces, are used to teach these concepts, making the learning process more intuitive and less about crunching numbers. While advanced topics like calculus or statistics may come into play later in more specialized areas, they’re not required upfront. So, don’t worry, if you’ve got a solid grasp of basic math and a logical mindset, you’re good to go!
Our course makes AI math-friendly and practical. Join now.
4. AI Is Only for Big Tech Companies
Now that’s not true because AI is transforming industries across the board! Whether it’s healthcare using AI to diagnose diseases, retail implementing recommendation systems for personalized shopping experiences, banking using AI to detect fraud, or education leveraging AI to personalize learning, the possibilities are endless.
In India, AI is booming in startups and government sectors alike. For example, companies like ZestMoney are using AI for better financial inclusion, while the Indian government is utilizing AI in smart city projects and disaster management. Additionally, your B.Sc. in IT (AI) can open doors to internships and placements with top companies in these industries. The scope of AI is vast, and with the right training, you can be part of its growth in any sector!
5. AI Will Replace All Jobs
The reality is, AI isn’t replacing jobs, it’s creating a lot more opportunities! According to the World Economic Forum, AI will create 170 million new jobs by 2025. These aren’t just tech-related roles either; industries are seeing demand for positions like AI Trainer, Prompt Engineer, Data Analyst, and even AI Ethics Specialist. The key is learning how to work alongside AI rather than being replaced by it.
Programs like B.Sc in IT (AI) are designed to teach you how to leverage AI tools to improve your skills and productivity, not just automate your job. By gaining a solid understanding of how AI works and how to apply it effectively, you’ll be in a great position to thrive in the AI-driven job market. The future isn’t about being replaced; it’s about collaboration with AI to drive innovation.
AI won’t replace you, but someone trained in AI might. Get skilled today.
6. AI Means Robotics Only
AI isn’t just about physical robots; it powers many of the software-based systems we use every day. From chatbots that assist with customer service, to search engines that help us find information, to voice assistants like Siri and Alexa, AI is behind these systems, making our lives easier and more efficient.
The key difference here is that AI refers to the technology that allows machines to learn and make decisions, while robotics focuses on building physical machines that can perform tasks. In your B.Sc in IT (AI), you’ll dive deep into software-focused AI, covering machine learning, natural language processing, and AI in applications like recommendation systems and predictive analytics topics that focus entirely on software, not robots.
Learn how AI is behind the apps you use daily. Start learning AI now.
7. You Need a High-End Laptop to Study AI
NO! You don’t need a high-end device to begin your AI learning! You can get started with just a basic laptop, using cloud tools and campus resources. In your B.Sc. in IT (AI) program, you’ll use tools like Google Colab, Jupyter Notebooks, and Python libraries to write and test code. These tools are free, accessible, and powerful enough for AI development.
Plus, many campuses offer state-of-the-art labs with the necessary infrastructure, including high-performance computers and cloud computing resources, to support your AI projects. So, whether you’re working from home or the campus lab, you’ll have everything you need to kickstart your AI learning.
We provide the tools — you bring the curiosity. Apply today
8. AI Is Too Advanced for College Students
AI might sound intimidating, but modern B.Sc programs are specifically designed to teach it at an undergraduate level, starting with the basics. The course structure is beginner-friendly, guiding you step by step through your learning journey.
In your first year, you will only study the fundamentals of learning programming, algorithms, and basic AI concepts like data structures. By the 2nd year, you’ll dive into tools and techniques, such as machine learning, Python programming, and data analysis. And in your 3rd and 4th year, you’ll apply what you’ve learned by working on real-world projects and exploring advanced applications like natural language processing and AI in business. With this gradual approach, AI becomes much more accessible, and you’ll feel confident as you advance through each stage of the course.
No experience needed — just a willingness to learn. Explore our AI program
9. AI Courses Are Too Expensive
Many people think AI courses are out of their budget, but the truth is, quality AI education is affordable and widely accessible, with plenty of options for financial aid and scholarships. For example, the course fees for the B.Sc in IT (AI) are much more reasonable compared to many specialized tech programs. Plus, there are scholarships available to help students based on merit or financial need, making it easier to get started without worrying about cost.
When you consider the return on investment, studying AI offers enormous potential. AI professionals are in high demand across industries like healthcare, finance, and tech, and the average salary for AI-related roles often far exceeds those of other fields. Investing in AI education now can lead to a rewarding, high-paying career in the future.
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10. AI Will Become Obsolete Soon
Far from becoming obsolete, AI is just getting started and is already the foundation of Industry 4.0, the next wave of technological advancement. AI’s impact is only going to grow. Automation, AI in healthcare (for better diagnosis and personalized treatments), AI in education (personalized learning experiences), and even ChatGPT (revolutionizing how we interact with machines) are just a few examples of how AI is reshaping industries and society. Far from being a passing trend, AI is a key driver of innovation that will continue to evolve and open up new career opportunities for years to come.
Why You Should Start Learning AI Now?
Now that we’ve busted the common myths, it is clear that AI is accessible, affordable, and, most importantly, full of opportunity. Whether you’re from a non-science background, don’t have advanced math skills, or don’t think you need coding experience, AI is for everyone.
The demand for AI professionals is skyrocketing, and it’s only going to increase as more industries adopt AI for everything from healthcare to retail to finance. The right time to start is now, right after your higher secondary education. Starting early means you can build strong foundations and step into the future with confidence, armed with skills that will be in high demand for years to come.
