How Beginners Can Learn AI in 2024: A 12-Month Roadmap

Last updated by Rishabh Dev Choudhary on Aug 09, 2024 at 11:50 AM | Reading time: 9 minutes

What Is Artificial Intelligence?

Considering that you are taking your first steps to learning AI, let’s start with the very basics of this technology. AI is a field of computer science that makes computers capable of performing tasks as intelligently as humans do, without being reprogrammed.

AI enables machines to perform tasks like decision-making, pattern recognition, understanding natural language, and self-learning through experience. There are various subfields of artificial intelligence with each demonstrating unique specializations.

What are the Types of Artificial Intelligence?

Artificial Intelligence can be classified into three categories:

● Artificial Narrow Intelligence (ANI: The Reality): Artificial Narrow Intelligence is the AI form we are living and experiencing today. An ANI instance can perform one task like providing shopping or movie recommendations, responding to requests, or resolving customer queries.

● Artificial General Intelligence (AGI: The Concept): It is a form of AI that demonstrates or will demonstrate expertise to perform various tasks with the same intelligence as humans do. Although many consider the current-day LLMs to be on par with AGI. many AI experts are of the view that AGI is still a concept.

● Artificial Super Intelligence (ASI: The Concept): It is a stage of AI that would come when it will supersede the capabilities and intelligence levels of humans. Only time will tell as to how potent or capable will ASI be as in this day and age it’s a concept worthy of deep analysis and study.

What Are the Subfields of AI?

As a beginner, before you know how to learn AI, you must first gain an understanding of its various subfields. Most career aspirants choose one of the following fields to specialize in:

● Machine Learning: This is a subfield of AI focused on developing algorithms that impart the ability to machines to self-learn without being explicitly reprogrammed.

● Deep Learning: It is a subfield of AI that uses multiple neural networks to simulate the complex decision-making of a human brain. Called deep learning networks, they form the backbone of a lot of AI applications currently being developed or used around the world.

● Natural Language Processing: This is a subfield of AI that enables machines to perform repetitive tasks like responding to human inputs on their own, without being explicitly reprogrammed to perform such tasks.

● Data Science: This is an interdisciplinary field that operates at the intersection of all three subfields of AI. It combines math, statistics, programming, data visualization, data analytics, and machine learning skills to uncover useful insights from the company’s data.

Why Should Beginners Learn AI?

Before figuring out how to learn AI, beginners should first understand why to learn AI. There is an ever-growing excitement around AI, making it an essential skill to learn.

Here are the three main reasons to learn AI:

● Global Transformation: AI has the potential to transform the world around us with applications in healthcare, robotics, drug discovery, tech, and finance. The market size of AI is expected to reach $17,50000 million US dollars by 2050. So, it’s a field worth exploring.

● Expanding Job Market: The demand for professionals skilled in AI is rapidly increasing. By 2030, 97 million new AI-driven jobs will be created. Since the transformation is just starting, it’s the best time for beginners to learn AI.

● AI Is Challenging & Rewarding: To learn AI is rewarding as it gives the learners a competitive edge over others. However, learning AI is challenging as one needs to learn a plethora of new skills to get started.

As AI is constantly evolving, continuous learning is crucial to keep pace with advancements in this field.

How Much Time Does It Take to Learn AI?

Beginners can take various routes to learn AI. They can either adopt a self-study route to become proficient through dedication and effort or through formal education by pursuing a relevant course in one of the AI disciplines or a university program.

Beginners often need to know the time it would take to learn AI. The answer may vary from person to person.

For someone who already has the basic knowledge of programming and mathematics, it may take close to 3-6 months of consistent study to master the basic AI skills. For more specialized knowledge of advanced AI concepts, one may require another 6-12 months of dedicated study.

Another factor to consider is the specialized field of AI one needs to pursue a career in. For instance, if one wants to become a data scientist he may not require a deep understanding of advanced machine learning algorithms. Still, a strong base in mathematics, data analytics, and data visualization tools is crucial.

One may also consider pursuing a specialized course in any field related to artificial intelligence. This comprehensive course covers every aspect of that specialized field from basic concepts to advanced topics.

In addition, that course should also prepare AI career aspirants for interviews with top-tier companies across the world.

If one plans to opt for the university route, specialized education of 3-4 years would be required in fields like data science, computer science, or a related field.

How to Learn AI From Scratch?

How to Learn AI From the very beginning? AI is a broad field that includes various sub-topics. One requires the right approach with a clear strategy to learn the skills effectively. Here is the step-by-step guide to follow to learn Ai from the beginning:

Learn the Prerequisites: Basic understanding of linear algebra, calculus, and probability is essential. In addition, concepts like distribution, regression, and likelihood are important to learn AI.

Master Specific AI Skills: Now that we’ve learned the basic AI skills, the next step is to learn specific skills to master AI. These skills will depend on the type of AI specialization you wish to pursue:

● To implement AI, one needs to have a sound understanding of programming with Python as it’s simple to use, flexible and has plenty of libraries and frameworks preinstalled.

● Knowledge of data structures like arrays, linked lists, stacks, and queues, is essential for writing efficient code.

● One must also learn data manipulation techniques like cleaning, transforming, and manipulating data for further analysis and feeding them in AI algorithms.

● It’s equally important to learn the tools, algorithms, and machine learning principles to extract insights from available data.

● Knowledge of different machine learning algorithms, how they work, and understanding complex patterns in datasets used in neural networks is also crucial for a broad understanding of various AI concepts.

Learn AI Tools and Principles: After gaining a broad understanding of AI principles, the next step is to learn top AI tools and packages needed to master AI skills:

● Knowledge of libraries and frameworks like Pandas, Numpy, Scikit-Learn, PyCaret, PyTorch, and Keras.

● Knowledge to utilize APIs to access commercially available models such as OpenAI API, Cohere API, and Anthropic API is a good way to start.

● Once you’ve gained proficiency with APIs, we can switch to advanced APIs like Hugging Face, and Langchain.

12 Month Roadmap for Beginners to Learn AI

Here is the learning plan beginners can adapt to learn AI. However, beginners can use their specific timelines and progress graphs to proceed with their AI learning.

● Month 1 to 3: Start with the basics of mathematics, statistics, programming languages, and data manipulation techniques.

● Month 4 to 6: Start with the basics of AI and then deepen your skills in machine learning and Generative AI. Consider pursuing an Applied Gen AI course that provides detailed knowledge of generative AI concepts.

● Month 7-9: Get a detailed understanding of neural networks, deep learning concepts, and MLOps. Based on your interests and career aspirations, consider specializing in one area.

● Month 10 and Beyond: Continue your learning by attending webinars, reading journals, and watching podcasts. Join various AI communities to gain insights into the latest trends and developments in the AI field.

Learn AI With Interview Kickstart!

With AI transforming various industries every passing day, learning it is crucial for beginners. Interview Kickstart, a global leader in career uplevelling has set a gold standard in AI education.

Our data science course covers everything from basics of mathematics, SQL programming, and Python, to advanced machine learning and deep learning concepts.

If you have a special affinity towards working with algorithms to train machines, our machine learning course is ideal for you.

Once you’ve gained ample understanding of all AI concepts get a deeper understanding of the AI topics with the MLOPs Training course or the Advanced Gen AI course.

Our courses are designed and taught by FAANG instructors. who have several years of experience working with top-tier companies.

The success stories of our students are a testament to how our courses are helping them transition to the AI domain.

FAQs: How to Learn AI for Beginners

1. Is Coding a Must-Have Skill to Learn AI?

No, coding is not a must-have skill to learn AI for beginners and for professionals as well. You can learn AI without coding by using user-friendly tools like Google Cloud AI Platform, IBM Watson, and Microsoft Azure Machine Learning Studio.

2. Is Python Necessary For AI?

Python is a prerequisite for learning AI. Anyone who wants to build a career in AI must understand Python well. It's simple to learn and use, is versatile, and has many libraries and frameworks that make it feature-rich.

3. Can a Non-IT Person Learn AI?

Anyone with the right attitude, the right resources in place, and the desire to learn can master AI. AI education is easy and can be learned through online courses as well, These courses build strong knowledge of AI and prepare you well for a rewarding career.

4. Can AI Replace the Human Brain?

Can AI replace the human brain? Well, the same question was asked when computers became a reality. AI can never replace humans as AI is the creation of humans.

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