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How do I start my Artificial Intelligence journey from scratch ?
Give me the complete road map for it
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Updated
Michelle’s Answer
Hello, Srishti !
So you want to go into the AI field. I hope that if I describe the path that is happening in America for this career that you can have an idea of how it may be going for you in your country.
Right at this current time, there are no college major courses of study for Artificial Intelligence, however, people usually major in other subjects and get jobs with AI. Some of the majors that people intending to be an AI professional major in are Computer Science, Math, Electrical Engineering, Data Science or Statistics. So you have a choice of majors for college. So do you need a college degree ?
Well, not having a college degree may not exactly eliminate your chances for an AI job, but doing a sort of quickie training on line scenario will not guarantee that you'd be chosen for an AI job either. Since that is the case, I would definitely advise that you go for a degree and I would suggest Computer Science or Data Science - at least a Bachelors Degree. The investment in a formal education and having the degree will pay off most likely better than any other route.
Let's talk about the skills you will need in order to work in an AI field. You will need computer programming skills, must be innovative, an abstract thinker and have superb problem solving skills. You also must be very passionate about going into this field of work.
Once you graduate with your degree, you would than do an internship and create a portfolio of your work that you have accomplished. Look into how AI professionals create their portfolios on line.
So that's the road map but stops at your avenue. It will all be up to you. If you decide to go to college, you will meet many people to network with and collaborate with. You will also have professors that will give you vital and updated information about current trends and developments with AI, so all the more essential to consider going to college for this.
I hope that this has been of some help and I wish you all the best with choosing a study and career path !
So you want to go into the AI field. I hope that if I describe the path that is happening in America for this career that you can have an idea of how it may be going for you in your country.
Right at this current time, there are no college major courses of study for Artificial Intelligence, however, people usually major in other subjects and get jobs with AI. Some of the majors that people intending to be an AI professional major in are Computer Science, Math, Electrical Engineering, Data Science or Statistics. So you have a choice of majors for college. So do you need a college degree ?
Well, not having a college degree may not exactly eliminate your chances for an AI job, but doing a sort of quickie training on line scenario will not guarantee that you'd be chosen for an AI job either. Since that is the case, I would definitely advise that you go for a degree and I would suggest Computer Science or Data Science - at least a Bachelors Degree. The investment in a formal education and having the degree will pay off most likely better than any other route.
Let's talk about the skills you will need in order to work in an AI field. You will need computer programming skills, must be innovative, an abstract thinker and have superb problem solving skills. You also must be very passionate about going into this field of work.
Once you graduate with your degree, you would than do an internship and create a portfolio of your work that you have accomplished. Look into how AI professionals create their portfolios on line.
So that's the road map but stops at your avenue. It will all be up to you. If you decide to go to college, you will meet many people to network with and collaborate with. You will also have professors that will give you vital and updated information about current trends and developments with AI, so all the more essential to consider going to college for this.
I hope that this has been of some help and I wish you all the best with choosing a study and career path !
Updated
Rihem’s Answer
Hello Srishti,
Starting your artificial intelligence (AI) journey from scratch can be both exciting and rewarding. Here are the essential steps to begin your AI journey:
Understand the Basics:
Begin by developing a solid understanding of what AI is. AI is a broad field that encompasses machine learning, deep learning, natural language processing, and more. Familiarize yourself with these concepts to know what you're getting into.
Learn Programming:
AI development often requires coding. Start with a language like Python, which is widely used in AI and machine learning. There are numerous online tutorials and courses to get you started.
Mathematics and Statistics:
AI heavily relies on mathematics and statistics. Focus on linear algebra, calculus, probability, and statistics. These concepts are the building blocks of AI algorithms.
Machine Learning:
Dive into machine learning, which is a subfield of AI. Study fundamental algorithms, such as linear regression, decision trees, and clustering. Online courses, like those on Coursera or edX, can provide structured learning paths.
Deep Learning:
To work on cutting-edge AI projects, delve into deep learning. This involves neural networks and requires a solid understanding of calculus, linear algebra, and Python. The "Deep Learning Specialization" on Coursera is a great resource.
Hands-On Projects:
Apply your knowledge by working on practical AI projects. Start with simple tasks like image classification or text analysis, and gradually move to more complex projects.
AI Frameworks and Tools:
Get comfortable with AI frameworks like TensorFlow and PyTorch, which are essential for developing AI models. Learn how to use libraries like scikit-learn for traditional machine learning.
Stay Informed:
AI is a rapidly evolving field. Follow AI news, blogs, and research papers to stay up-to-date with the latest developments. Websites like arXiv and conferences like NeurIPS are good sources.
Online Courses and Certifications:
Enroll in online courses and certifications. Platforms like Coursera, edX, and Udacity offer AI-related programs, some of which are taught by top universities.
Join AI Communities:
Engage with AI communities on platforms like GitHub, Stack Overflow, and Reddit. Participating in discussions, sharing your work, and seeking feedback can be immensely helpful.
Build a Portfolio:
Create a portfolio showcasing your AI projects and experiments. A well-documented portfolio is crucial for job applications or freelance opportunities.
Specialize:
AI is diverse. Consider specializing in a specific area like computer vision, natural language processing, or reinforcement learning to deepen your expertise.
Higher Education (Optional):
If you want a formal education, you can pursue a bachelor's or master's degree in AI or related fields like computer science or data science. This is optional but can be valuable.
Networking:
Attend AI-related meetups, conferences, and workshops. Networking can lead to collaboration opportunities and job referrals.
Practice Ethical AI:
Learn about the ethical considerations in AI and ensure your projects adhere to responsible AI principles.
Starting your AI journey from scratch will require dedication, perseverance, and continuous learning. Keep practicing, stay curious, and remember that AI is a field where experimentation and creativity are highly valued.
Starting your artificial intelligence (AI) journey from scratch can be both exciting and rewarding. Here are the essential steps to begin your AI journey:
Understand the Basics:
Begin by developing a solid understanding of what AI is. AI is a broad field that encompasses machine learning, deep learning, natural language processing, and more. Familiarize yourself with these concepts to know what you're getting into.
Learn Programming:
AI development often requires coding. Start with a language like Python, which is widely used in AI and machine learning. There are numerous online tutorials and courses to get you started.
Mathematics and Statistics:
AI heavily relies on mathematics and statistics. Focus on linear algebra, calculus, probability, and statistics. These concepts are the building blocks of AI algorithms.
Machine Learning:
Dive into machine learning, which is a subfield of AI. Study fundamental algorithms, such as linear regression, decision trees, and clustering. Online courses, like those on Coursera or edX, can provide structured learning paths.
Deep Learning:
To work on cutting-edge AI projects, delve into deep learning. This involves neural networks and requires a solid understanding of calculus, linear algebra, and Python. The "Deep Learning Specialization" on Coursera is a great resource.
Hands-On Projects:
Apply your knowledge by working on practical AI projects. Start with simple tasks like image classification or text analysis, and gradually move to more complex projects.
AI Frameworks and Tools:
Get comfortable with AI frameworks like TensorFlow and PyTorch, which are essential for developing AI models. Learn how to use libraries like scikit-learn for traditional machine learning.
Stay Informed:
AI is a rapidly evolving field. Follow AI news, blogs, and research papers to stay up-to-date with the latest developments. Websites like arXiv and conferences like NeurIPS are good sources.
Online Courses and Certifications:
Enroll in online courses and certifications. Platforms like Coursera, edX, and Udacity offer AI-related programs, some of which are taught by top universities.
Join AI Communities:
Engage with AI communities on platforms like GitHub, Stack Overflow, and Reddit. Participating in discussions, sharing your work, and seeking feedback can be immensely helpful.
Build a Portfolio:
Create a portfolio showcasing your AI projects and experiments. A well-documented portfolio is crucial for job applications or freelance opportunities.
Specialize:
AI is diverse. Consider specializing in a specific area like computer vision, natural language processing, or reinforcement learning to deepen your expertise.
Higher Education (Optional):
If you want a formal education, you can pursue a bachelor's or master's degree in AI or related fields like computer science or data science. This is optional but can be valuable.
Networking:
Attend AI-related meetups, conferences, and workshops. Networking can lead to collaboration opportunities and job referrals.
Practice Ethical AI:
Learn about the ethical considerations in AI and ensure your projects adhere to responsible AI principles.
Starting your AI journey from scratch will require dedication, perseverance, and continuous learning. Keep practicing, stay curious, and remember that AI is a field where experimentation and creativity are highly valued.
Updated
Amalorpavaraj’s Answer
Starting a career in artificial intelligence (AI) in India is an exciting prospect, as the field is rapidly growing and offers numerous opportunities. Here are steps to help you begin your AI career in India:
Develop a Strong Educational Foundation:
Begin with a strong educational background. A bachelor's degree in computer science, mathematics, or a related field is a good starting point. Pursuing a master's or PhD can provide deeper expertise and open up advanced opportunities.
Learn the Basics of AI:
Familiarize yourself with the fundamentals of AI, including machine learning, deep learning, natural language processing, and computer vision. Online courses and tutorials can help you get started. Platforms like Coursera, edX, and Udemy offer numerous AI courses.
Choose a Specialization:
AI is a broad field. Decide on a specific area to specialize in, such as data science, machine learning, computer vision, or natural language processing. Your choice may influence the skills and tools you need to learn.
Gain Programming Skills:
Become proficient in programming languages commonly used in AI, such as Python and R. Learn how to work with libraries and frameworks like TensorFlow and PyTorch.
Understand Data:
AI relies on data. Learn how to collect, clean, preprocess, and analyze data. Knowledge of data engineering and data science is valuable.
Online Courses and Certifications:
Consider taking online courses or obtaining certifications in AI. These can add credibility to your resume and demonstrate your expertise.
Apply for Internships:
Look for AI internships in Indian companies or research institutions. Internships provide hands-on experience and can lead to full-time job opportunities.
Stay Updated:
AI is an ever-evolving field. We are moving from tradition AI to Gen AI now. Keep learning and stay updated on the latest developments, research, and technologies.
India has a growing AI industry with many job opportunities in cities like Bangalore, Hyderabad, and Pune. Apply for internship and short term projects/assignments. By following these steps, you can work towards building a successful AI career in India.
All the best.
Develop a Strong Educational Foundation:
Begin with a strong educational background. A bachelor's degree in computer science, mathematics, or a related field is a good starting point. Pursuing a master's or PhD can provide deeper expertise and open up advanced opportunities.
Learn the Basics of AI:
Familiarize yourself with the fundamentals of AI, including machine learning, deep learning, natural language processing, and computer vision. Online courses and tutorials can help you get started. Platforms like Coursera, edX, and Udemy offer numerous AI courses.
Choose a Specialization:
AI is a broad field. Decide on a specific area to specialize in, such as data science, machine learning, computer vision, or natural language processing. Your choice may influence the skills and tools you need to learn.
Gain Programming Skills:
Become proficient in programming languages commonly used in AI, such as Python and R. Learn how to work with libraries and frameworks like TensorFlow and PyTorch.
Understand Data:
AI relies on data. Learn how to collect, clean, preprocess, and analyze data. Knowledge of data engineering and data science is valuable.
Online Courses and Certifications:
Consider taking online courses or obtaining certifications in AI. These can add credibility to your resume and demonstrate your expertise.
Apply for Internships:
Look for AI internships in Indian companies or research institutions. Internships provide hands-on experience and can lead to full-time job opportunities.
Stay Updated:
AI is an ever-evolving field. We are moving from tradition AI to Gen AI now. Keep learning and stay updated on the latest developments, research, and technologies.
India has a growing AI industry with many job opportunities in cities like Bangalore, Hyderabad, and Pune. Apply for internship and short term projects/assignments. By following these steps, you can work towards building a successful AI career in India.
All the best.
Updated
Biju’s Answer
Breaking into the world of AI can be both exciting and rewarding, especially given the rapid advancements in the field. There are several roles that work closely with AI, each offering unique opportunities to shape the future of technology.
As a Machine Learning Engineer, you would be responsible for developing algorithms that allow machines to learn from data. This role requires a solid foundation in programming languages like Python or R and experience with AI frameworks such as TensorFlow or PyTorch. A degree in computer science or machine learning, often at the master’s level, is typically needed for this position.
On the other hand, if you’re drawn to data, becoming a Data Scientist might be the right fit. Data scientists analyze large datasets, uncovering trends and insights using machine learning models. This job combines statistical analysis, coding, and data visualization skills. A bachelor's degree in data science or computer science can get you started, though many in the field hold advanced degrees.
For those more interested in research, working as an AI Research Scientist offers the chance to push the boundaries of AI theory. Whether developing new algorithms or improving existing ones, this role usually requires a Ph.D. in AI or machine learning, along with expertise in deep learning and reinforcement learning.
If your passion lies in creating real-world AI systems, a Software Engineer specializing in AI integrates machine learning models into software applications. A strong software development background, along with knowledge of AI tools, is key, and a bachelor’s in software engineering or computer science is often the starting point.
AI also plays a central role in robotics, so if you’re fascinated by machines, you could become a Robotics Engineer. In this role, you would design autonomous systems, combining AI with mechanical engineering and sensor technology.
To prepare for an AI career:
A bachelor’s degree in computer science, data science, or a related field is typically the foundation.
Pursuing a master’s degree in AI, machine learning, or data science can help you advance.
Online courses and certifications in AI and machine learning (from platforms like Coursera or Google TensorFlow) are valuable for gaining specific technical skills.
For research roles, a Ph.D. in AI is often necessary.
Getting hands-on experience, whether through internships or personal projects, is just as critical as formal education. AI is a field where curiosity, creativity, and a hunger to learn are as important as technical knowledge. So, no matter the path, embracing continuous learning will help you thrive in this rapidly evolving landscape.
As a Machine Learning Engineer, you would be responsible for developing algorithms that allow machines to learn from data. This role requires a solid foundation in programming languages like Python or R and experience with AI frameworks such as TensorFlow or PyTorch. A degree in computer science or machine learning, often at the master’s level, is typically needed for this position.
On the other hand, if you’re drawn to data, becoming a Data Scientist might be the right fit. Data scientists analyze large datasets, uncovering trends and insights using machine learning models. This job combines statistical analysis, coding, and data visualization skills. A bachelor's degree in data science or computer science can get you started, though many in the field hold advanced degrees.
For those more interested in research, working as an AI Research Scientist offers the chance to push the boundaries of AI theory. Whether developing new algorithms or improving existing ones, this role usually requires a Ph.D. in AI or machine learning, along with expertise in deep learning and reinforcement learning.
If your passion lies in creating real-world AI systems, a Software Engineer specializing in AI integrates machine learning models into software applications. A strong software development background, along with knowledge of AI tools, is key, and a bachelor’s in software engineering or computer science is often the starting point.
AI also plays a central role in robotics, so if you’re fascinated by machines, you could become a Robotics Engineer. In this role, you would design autonomous systems, combining AI with mechanical engineering and sensor technology.
To prepare for an AI career:
A bachelor’s degree in computer science, data science, or a related field is typically the foundation.
Pursuing a master’s degree in AI, machine learning, or data science can help you advance.
Online courses and certifications in AI and machine learning (from platforms like Coursera or Google TensorFlow) are valuable for gaining specific technical skills.
For research roles, a Ph.D. in AI is often necessary.
Getting hands-on experience, whether through internships or personal projects, is just as critical as formal education. AI is a field where curiosity, creativity, and a hunger to learn are as important as technical knowledge. So, no matter the path, embracing continuous learning will help you thrive in this rapidly evolving landscape.
Updated
Alex’s Answer
Hi Srishti,
Part of it is really being passionate and figuring out your own path.
AI is so broad to begin with and now the field is evolving so quickly it's hard to keep up. I majored in AI and ML 12 years ago and still haven't had a chance to use it professionally yet, now I'm worried it's all obsolete. I'm taking udemy courses during work hours just trying to stay up to date.
There's a guy who blogs about this topic that might answer your question better than me or anyone. Look up Matt Champan on "Towards Data Science". My favorite one is "How do I stay up to date with the latest AI trends" but he has a bunch of others.
My key takeaway from his blogs is that to get into AI from another field or while working a full-time job, you (somehow) need to carve out time for personal projects and create your own personal portfolio. If you showcase different areas of expertise and learn how to tell a convincing story, or solve a problem, this can count for more than any resume.
Basic first step "from scratch" is a computer science degree if you don't have one. That means 3-4 years of study. Major or specialize in subjects such as neural networks. From there it's about continuous learning - as with any skill or profession.
Part of it is really being passionate and figuring out your own path.
AI is so broad to begin with and now the field is evolving so quickly it's hard to keep up. I majored in AI and ML 12 years ago and still haven't had a chance to use it professionally yet, now I'm worried it's all obsolete. I'm taking udemy courses during work hours just trying to stay up to date.
There's a guy who blogs about this topic that might answer your question better than me or anyone. Look up Matt Champan on "Towards Data Science". My favorite one is "How do I stay up to date with the latest AI trends" but he has a bunch of others.
My key takeaway from his blogs is that to get into AI from another field or while working a full-time job, you (somehow) need to carve out time for personal projects and create your own personal portfolio. If you showcase different areas of expertise and learn how to tell a convincing story, or solve a problem, this can count for more than any resume.
Basic first step "from scratch" is a computer science degree if you don't have one. That means 3-4 years of study. Major or specialize in subjects such as neural networks. From there it's about continuous learning - as with any skill or profession.
Updated
Amit’s Answer
Dear Srishti,
Embarking on your exploration of Artificial Intelligence (AI) entails a series of steps. Let's walk through this roadmap together:
Firstly, Grasp the Concept of AI: AI is a specialized sector of computer science that aims to develop systems capable of executing tasks typically necessitating human intelligence. These tasks encompass understanding human language, identifying patterns, making decisions, and learning from past experiences.
Next, Familiarize Yourself with the Various Forms of AI: AI can be classified into three categories based on its abilities:
1. Artificial Narrow Intelligence (ANI): This type of AI is engineered to carry out a singular task, such as voice recognition or suggesting content on streaming platforms.
2. Artificial General Intelligence (AGI): An AI that exhibits AGI has the capacity to comprehend, learn, adapt, and apply knowledge across a broad spectrum of tasks at a human level.
3. Artificial Super Intelligence (ASI): This is a future concept where AI surpasses human intelligence in almost all economically beneficial tasks.
Then, Distinguish Between Data Science, AI, Machine Learning, and Deep Learning: AI is a component of the data science field and involves crafting computer programs that can replicate tasks linked to human intelligence. Machine learning, deep learning, and natural language processing are sub-disciplines of AI that enable computers to "learn" from past experiences and carry out tasks similar to humans.
Now, Begin Your Learning Journey: There's a wealth of resources available online to kickstart your AI journey. Comprehensive tutorials for beginners can be found on platforms like YouTube, Udemy, and others.
Afterwards, Apply and Execute: The most effective way to learn is through practice. Endeavor to apply what you've learned in mini-projects. This will not only reinforce your understanding of the concepts but also contribute to your portfolio.
Lastly, Stay Informed: AI is a swiftly progressing field. Stay abreast with the latest research papers, articles, and news.
Bear in mind, mastering AI is a journey. It demands time, patience, and unwavering effort. Best of luck on your journey! 🚀
Embarking on your exploration of Artificial Intelligence (AI) entails a series of steps. Let's walk through this roadmap together:
Firstly, Grasp the Concept of AI: AI is a specialized sector of computer science that aims to develop systems capable of executing tasks typically necessitating human intelligence. These tasks encompass understanding human language, identifying patterns, making decisions, and learning from past experiences.
Next, Familiarize Yourself with the Various Forms of AI: AI can be classified into three categories based on its abilities:
1. Artificial Narrow Intelligence (ANI): This type of AI is engineered to carry out a singular task, such as voice recognition or suggesting content on streaming platforms.
2. Artificial General Intelligence (AGI): An AI that exhibits AGI has the capacity to comprehend, learn, adapt, and apply knowledge across a broad spectrum of tasks at a human level.
3. Artificial Super Intelligence (ASI): This is a future concept where AI surpasses human intelligence in almost all economically beneficial tasks.
Then, Distinguish Between Data Science, AI, Machine Learning, and Deep Learning: AI is a component of the data science field and involves crafting computer programs that can replicate tasks linked to human intelligence. Machine learning, deep learning, and natural language processing are sub-disciplines of AI that enable computers to "learn" from past experiences and carry out tasks similar to humans.
Now, Begin Your Learning Journey: There's a wealth of resources available online to kickstart your AI journey. Comprehensive tutorials for beginners can be found on platforms like YouTube, Udemy, and others.
Afterwards, Apply and Execute: The most effective way to learn is through practice. Endeavor to apply what you've learned in mini-projects. This will not only reinforce your understanding of the concepts but also contribute to your portfolio.
Lastly, Stay Informed: AI is a swiftly progressing field. Stay abreast with the latest research papers, articles, and news.
Bear in mind, mastering AI is a journey. It demands time, patience, and unwavering effort. Best of luck on your journey! 🚀
Updated
Amalya’s Answer
Your chosen field is very demanded, time-efficient and interesting. To start getting into the field, you can do a variety of things. You can get academic background if you have long-term career goals in this discipline. You can check this link to find Bachelor of Science in Artificial Intelligence and other programs related to the field: https://www.bachelorstudies.com/bsc/artificial-intelligence/usa
You can also use the internet as a means to get great resources, self-study materials, various courses, and much more.
One more option: If you are interested, there are opportunities to take part in internships and virtual work experience programs.
You can also use the internet as a means to get great resources, self-study materials, various courses, and much more.
One more option: If you are interested, there are opportunities to take part in internships and virtual work experience programs.