9 answers
Muhammed
Student
Indore, Madhya Pradesh, India
1
Question
Asked
5471 views
What is the best route of becoming an AI Engineer?
I am a 17 year old boy, a self taught programmer in python, C++ and C# and a 3d artist with professional certificate. I want to show this world a better and ease future with the aid of AI technology and virtual reality. I am looking for a guide to help me enroll in an AI course as a degree.
thank you
have a wonderful day😊
Login to comment
9 answers
Rolando Caraballo
7
Answers
Knoxville, Tennessee
Updated
Rolando’s Answer
Start you own project. Built a portfolio. If you really know, C++ and C# and a 3d artist(no Copy and paste). One option that doesn't involve college is make a Video Game in Unreal. The game industry do not care if you have a degree or not. they care about your portfolio. Look for jobs on the game industry, and all way ask for recommendation in how to improve.
Thank you so much!
Muhammed
Abhishek Jain
Consulting
26
Answers
Ahmedabad, Gujarat, India
Updated
Abhishek’s Answer
Becoming an AI engineer requires a combination of technical skills, knowledge, and practical experience. Here's a guide to help you pursue a career in AI as an Indian student from Indore:
1. Education and Degree Programs: Pursuing a degree in a relevant field is a good starting point. Look for universities or colleges that offer undergraduate or postgraduate programs in computer science, artificial intelligence, machine learning, or data science. Research the curriculum, faculty expertise, and industry collaborations to find a program that aligns with your interests and goals.
2. Entrance Exams: In India, many universities and institutes require students to appear for entrance exams for admission to their AI or computer science programs. Common entrance exams include JEE Main, JEE Advanced, BITSAT, and various state-level engineering entrance exams. Prepare for these exams by studying the relevant subjects and practicing sample papers.
3. Online Courses and Certifications: Supplement your formal education with online courses and certifications in AI and related fields. Platforms like Coursera, edX, and Udacity offer a wide range of courses taught by experts from top universities and industry professionals. Some popular AI courses include "Machine Learning" by Andrew Ng and "Deep Learning Specialization" by deeplearning.ai.
4. Projects and Practical Experience: Gain practical experience by working on AI projects. Start with small projects to apply your programming skills and gradually move on to more complex projects involving machine learning, natural language processing, or computer vision. Building a portfolio of projects will demonstrate your skills and commitment to potential employers or universities.
5. Internships and Industry Exposure: Seek internships or part-time positions in companies or research labs that work on AI-related projects. This will provide you with hands-on experience, exposure to real-world applications, and an opportunity to network with professionals in the field.
6. Research and Publications: Engage in research activities by participating in conferences, workshops, or research programs. Collaborate with professors or researchers in your university or explore opportunities with research organizations. Publishing research papers or presenting your work at conferences can enhance your profile and open doors to advanced academic programs or industry positions.
7. Networking and Professional Organizations: Join AI-related professional organizations and attend industry events, conferences, and meetups. Networking with professionals in the field can provide valuable insights, mentorship opportunities, and potential job leads.
8. Continuous Learning: AI is a rapidly evolving field, so it's important to stay updated with the latest advancements and trends. Follow reputable AI blogs, research papers, and industry publications. Engage in continuous learning through online courses, workshops, and conferences to expand your knowledge and skills.
Remember, building a successful career in AI requires dedication, continuous learning, and practical experience. Be proactive in seeking opportunities, stay curious, and keep honing your skills. With the right mindset and effort, you can make a significant impact in the field of AI and contribute to a better future.
1. Education and Degree Programs: Pursuing a degree in a relevant field is a good starting point. Look for universities or colleges that offer undergraduate or postgraduate programs in computer science, artificial intelligence, machine learning, or data science. Research the curriculum, faculty expertise, and industry collaborations to find a program that aligns with your interests and goals.
2. Entrance Exams: In India, many universities and institutes require students to appear for entrance exams for admission to their AI or computer science programs. Common entrance exams include JEE Main, JEE Advanced, BITSAT, and various state-level engineering entrance exams. Prepare for these exams by studying the relevant subjects and practicing sample papers.
3. Online Courses and Certifications: Supplement your formal education with online courses and certifications in AI and related fields. Platforms like Coursera, edX, and Udacity offer a wide range of courses taught by experts from top universities and industry professionals. Some popular AI courses include "Machine Learning" by Andrew Ng and "Deep Learning Specialization" by deeplearning.ai.
4. Projects and Practical Experience: Gain practical experience by working on AI projects. Start with small projects to apply your programming skills and gradually move on to more complex projects involving machine learning, natural language processing, or computer vision. Building a portfolio of projects will demonstrate your skills and commitment to potential employers or universities.
5. Internships and Industry Exposure: Seek internships or part-time positions in companies or research labs that work on AI-related projects. This will provide you with hands-on experience, exposure to real-world applications, and an opportunity to network with professionals in the field.
6. Research and Publications: Engage in research activities by participating in conferences, workshops, or research programs. Collaborate with professors or researchers in your university or explore opportunities with research organizations. Publishing research papers or presenting your work at conferences can enhance your profile and open doors to advanced academic programs or industry positions.
7. Networking and Professional Organizations: Join AI-related professional organizations and attend industry events, conferences, and meetups. Networking with professionals in the field can provide valuable insights, mentorship opportunities, and potential job leads.
8. Continuous Learning: AI is a rapidly evolving field, so it's important to stay updated with the latest advancements and trends. Follow reputable AI blogs, research papers, and industry publications. Engage in continuous learning through online courses, workshops, and conferences to expand your knowledge and skills.
Remember, building a successful career in AI requires dedication, continuous learning, and practical experience. Be proactive in seeking opportunities, stay curious, and keep honing your skills. With the right mindset and effort, you can make a significant impact in the field of AI and contribute to a better future.
Patrick Meyer
Executive - Data Analytics and AI
780
Answers
Naperville, Illinois
Updated
Patrick’s Answer
Muhammed, I appreciate your interest in becoming an AI Engineer and your initiative in seeking advice. I'm hopeful that the following insights will be helpful to you.
You've already set a strong base for your AI Engineering career with your programming skills and 3D artistry experience. To further your journey, you should aim to understand artificial intelligence deeply, learning its concepts, algorithms, and techniques. You should also gain hands-on experience in applying AI technologies to solve real-world issues. Here's a step-by-step guide to help you:
• Start by exploring the theory and principles of artificial intelligence. Your proficiency in Python, C++, and C# gives you a strong programming foundation for AI development. Spend time learning key AI concepts like machine learning, neural networks, natural language processing, computer vision, and reinforcement learning. Online learning platforms such as Coursera, edX, and Udacity offer AI basic courses taught by top university and industry experts.
• Identify AI areas that match your interests and career goals, like machine learning, computer vision, or natural language processing. Consider joining specialized courses or certification programs that focus on these areas. These programs will provide you with deep knowledge and practical experience in using AI techniques to solve real-world issues. Look for programs that offer practical projects, case studies, and chances to work with industry-standard tools and libraries.
• Considering your interest in improving the future with AI technology and virtual reality, think about adding VR/AR to your skills. Learn about VR/AR development platforms, tools, and techniques, and explore how AI can improve experiences and interactions in virtual environments. Online resources, tutorials, and VR/AR development communities can provide valuable insights and guidance.
• Even though you're already skilled in programming and have a professional certification in 3D artistry, a formal AI education can offer you a structured curriculum, expert guidance, and a recognized degree to boost your credentials and career prospects. Look for universities or colleges that offer undergraduate or graduate programs in artificial intelligence, machine learning, or related fields. When choosing a program, consider the program's reputation, faculty expertise, research opportunities, and industry partnerships.
• As you advance in your AI education and gain practical experience, focus on creating a robust portfolio of projects that display your skills and achievements. Develop AI applications, algorithms, and models that show your ability to solve complex problems, analyze data, and effectively use AI technologies. Your portfolio will be a concrete demonstration of your expertise and creativity to potential employers or collaborators in the AI and VR industries.
By following this guide and continuously learning, exploring, and creating, you'll be well-prepared to become an AI Engineer and help build a better and more innovative future with AI technology and virtual reality. Always stay curious, persistent, and proactive in your quest for knowledge and skills. Don't hesitate to seek advice from mentors, educators, and professionals in the field.
You've already set a strong base for your AI Engineering career with your programming skills and 3D artistry experience. To further your journey, you should aim to understand artificial intelligence deeply, learning its concepts, algorithms, and techniques. You should also gain hands-on experience in applying AI technologies to solve real-world issues. Here's a step-by-step guide to help you:
• Start by exploring the theory and principles of artificial intelligence. Your proficiency in Python, C++, and C# gives you a strong programming foundation for AI development. Spend time learning key AI concepts like machine learning, neural networks, natural language processing, computer vision, and reinforcement learning. Online learning platforms such as Coursera, edX, and Udacity offer AI basic courses taught by top university and industry experts.
• Identify AI areas that match your interests and career goals, like machine learning, computer vision, or natural language processing. Consider joining specialized courses or certification programs that focus on these areas. These programs will provide you with deep knowledge and practical experience in using AI techniques to solve real-world issues. Look for programs that offer practical projects, case studies, and chances to work with industry-standard tools and libraries.
• Considering your interest in improving the future with AI technology and virtual reality, think about adding VR/AR to your skills. Learn about VR/AR development platforms, tools, and techniques, and explore how AI can improve experiences and interactions in virtual environments. Online resources, tutorials, and VR/AR development communities can provide valuable insights and guidance.
• Even though you're already skilled in programming and have a professional certification in 3D artistry, a formal AI education can offer you a structured curriculum, expert guidance, and a recognized degree to boost your credentials and career prospects. Look for universities or colleges that offer undergraduate or graduate programs in artificial intelligence, machine learning, or related fields. When choosing a program, consider the program's reputation, faculty expertise, research opportunities, and industry partnerships.
• As you advance in your AI education and gain practical experience, focus on creating a robust portfolio of projects that display your skills and achievements. Develop AI applications, algorithms, and models that show your ability to solve complex problems, analyze data, and effectively use AI technologies. Your portfolio will be a concrete demonstration of your expertise and creativity to potential employers or collaborators in the AI and VR industries.
By following this guide and continuously learning, exploring, and creating, you'll be well-prepared to become an AI Engineer and help build a better and more innovative future with AI technology and virtual reality. Always stay curious, persistent, and proactive in your quest for knowledge and skills. Don't hesitate to seek advice from mentors, educators, and professionals in the field.
James Constantine Frangos
Consultant Dietitian & Software Developer since 1972 => Nutrition Education => Health & Longevity => Self-Actualization.
6333
Answers
Gold Coast, Queensland, Australia
Updated
James Constantine’s Answer
Hello Muhammed,
Becoming an AI Engineer: A Comprehensive Guide
1. Pursue a Relevant Degree: To become an AI engineer, it is highly recommended to pursue a relevant degree in computer science, artificial intelligence, machine learning, data science, or a related field. Many universities offer undergraduate and graduate programs specifically tailored to AI and machine learning.
2. Gain Strong Programming Skills: Since you already have experience in Python, C++, and C#, you are on the right track. These programming languages are widely used in the field of AI. It is essential to continue honing your programming skills as they are fundamental for AI development.
3. Build a Strong Foundation in Mathematics: Mathematics forms the backbone of AI and machine learning. Concepts such as linear algebra, calculus, probability, and statistics are crucial for understanding algorithms and models used in AI. Strengthening your mathematical skills will be beneficial for your journey towards becoming an AI engineer.
4. Explore Online Courses and Resources: There are numerous online courses, tutorials, and resources available that can help you deepen your understanding of AI concepts and technologies. Platforms like Coursera, edX, Udacity, and Khan Academy offer courses on AI, machine learning, deep learning, and more.
5. Work on Projects and Build a Portfolio: Practical experience is invaluable in the field of AI. Start working on projects that showcase your skills and knowledge in AI and virtual reality. Building a strong portfolio will not only demonstrate your capabilities to potential employers but also provide you with hands-on experience.
6. Consider Specializations within AI: AI is a vast field with various specializations such as natural language processing, computer vision, robotics, etc. Explore different areas within AI to find what interests you the most and consider specializing in that particular domain.
7. Network with Professionals in the Field: Networking is essential for career growth. Attend conferences, workshops, meetups, and connect with professionals working in the AI industry. Building a network can open up opportunities for internships, mentorship, and collaborations.
8. Apply for Internships and Entry-Level Positions: Internships provide valuable real-world experience and can be a stepping stone towards a full-time position as an AI engineer. Look for internship opportunities at tech companies, research institutions, or startups working on AI projects.
9. Stay Updated with Industry Trends: The field of AI is rapidly evolving with new advancements and technologies emerging regularly. Stay updated with the latest trends, research papers, conferences, and developments in the field to remain competitive as an AI engineer.
10. Enroll in an AI Degree Program: Considering your passion for AI technology and virtual reality, look for universities or colleges offering degree programs specifically focused on artificial intelligence or related fields. Research their curriculum, faculty expertise, research opportunities, and industry connections before enrolling.
By following these steps diligently and continuously expanding your knowledge and skills in artificial intelligence and related technologies, you can pave the way towards a successful career as an AI engineer.
Top 3 Authoritative Sources Used:
Stanford University’s Online Courses: Stanford University offers online courses on artificial intelligence through platforms like Coursera which are taught by renowned professors in the field.
IEEE Xplore Digital Library: IEEE Xplore provides access to high-quality research articles, conference papers, and journals related to artificial intelligence and machine learning.
Towards Data Science: Towards Data Science is a popular platform that publishes articles, tutorials, and resources on various topics including artificial intelligence, machine learning, data science, etc., written by industry professionals and experts.
GOD BLESS!
James.
Becoming an AI Engineer: A Comprehensive Guide
1. Pursue a Relevant Degree: To become an AI engineer, it is highly recommended to pursue a relevant degree in computer science, artificial intelligence, machine learning, data science, or a related field. Many universities offer undergraduate and graduate programs specifically tailored to AI and machine learning.
2. Gain Strong Programming Skills: Since you already have experience in Python, C++, and C#, you are on the right track. These programming languages are widely used in the field of AI. It is essential to continue honing your programming skills as they are fundamental for AI development.
3. Build a Strong Foundation in Mathematics: Mathematics forms the backbone of AI and machine learning. Concepts such as linear algebra, calculus, probability, and statistics are crucial for understanding algorithms and models used in AI. Strengthening your mathematical skills will be beneficial for your journey towards becoming an AI engineer.
4. Explore Online Courses and Resources: There are numerous online courses, tutorials, and resources available that can help you deepen your understanding of AI concepts and technologies. Platforms like Coursera, edX, Udacity, and Khan Academy offer courses on AI, machine learning, deep learning, and more.
5. Work on Projects and Build a Portfolio: Practical experience is invaluable in the field of AI. Start working on projects that showcase your skills and knowledge in AI and virtual reality. Building a strong portfolio will not only demonstrate your capabilities to potential employers but also provide you with hands-on experience.
6. Consider Specializations within AI: AI is a vast field with various specializations such as natural language processing, computer vision, robotics, etc. Explore different areas within AI to find what interests you the most and consider specializing in that particular domain.
7. Network with Professionals in the Field: Networking is essential for career growth. Attend conferences, workshops, meetups, and connect with professionals working in the AI industry. Building a network can open up opportunities for internships, mentorship, and collaborations.
8. Apply for Internships and Entry-Level Positions: Internships provide valuable real-world experience and can be a stepping stone towards a full-time position as an AI engineer. Look for internship opportunities at tech companies, research institutions, or startups working on AI projects.
9. Stay Updated with Industry Trends: The field of AI is rapidly evolving with new advancements and technologies emerging regularly. Stay updated with the latest trends, research papers, conferences, and developments in the field to remain competitive as an AI engineer.
10. Enroll in an AI Degree Program: Considering your passion for AI technology and virtual reality, look for universities or colleges offering degree programs specifically focused on artificial intelligence or related fields. Research their curriculum, faculty expertise, research opportunities, and industry connections before enrolling.
By following these steps diligently and continuously expanding your knowledge and skills in artificial intelligence and related technologies, you can pave the way towards a successful career as an AI engineer.
Top 3 Authoritative Sources Used:
Stanford University’s Online Courses: Stanford University offers online courses on artificial intelligence through platforms like Coursera which are taught by renowned professors in the field.
IEEE Xplore Digital Library: IEEE Xplore provides access to high-quality research articles, conference papers, and journals related to artificial intelligence and machine learning.
Towards Data Science: Towards Data Science is a popular platform that publishes articles, tutorials, and resources on various topics including artificial intelligence, machine learning, data science, etc., written by industry professionals and experts.
GOD BLESS!
James.
I appreciate this, thank you for the advice.
Muhammed
Praveen B.S
14
Answers
Updated
Praveen’s Answer
To launch a successful career as an AI engineer, you need a blend of education, skill enhancement, and hands-on experience. Here's a practical guide to help you navigate this career path:
1. Lay the Educational Groundwork:
- Bachelor's Degree: Kick-off your journey with a bachelor's degree in a relevant field like computer science, mathematics, statistics, or engineering. Prioritize courses in artificial intelligence, machine learning, data science, computer programming, and algorithms.
- Master's Degree (Optional): If you're keen on advanced research or specialized applications, a master's degree in artificial intelligence, machine learning, or a related field can be a valuable addition.
2. Acquire Programming Skills:
- Familiarize yourself with programming languages frequently used in AI development, such as Python, R, and Java. Python is a favorite choice due to its vast libraries for AI and data science, including TensorFlow, PyTorch, and scikit-learn.
3. Become Proficient in Machine Learning and Deep Learning:
- Grasp the basics of machine learning algorithms, techniques, and methodologies. Get a handle on supervised learning, unsupervised learning, reinforcement learning, and deep learning.
- Delve into neural networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and other deep learning structures.
4. Build a Solid Mathematical Foundation:
- Enhance your mathematical skills, especially in linear algebra, calculus, probability, and statistics. These principles are crucial for understanding the mechanics of machine learning algorithms.
5. Engage in Projects:
- Get hands-on experience by undertaking AI projects. This could include crafting machine learning models, developing AI applications, or competing in Kaggle contests.
- Construct a portfolio to display your projects and exhibit your abilities to prospective employers or partners.
6. Stay Informed and Connect with the Community:
- Keep abreast of the latest trends in AI and machine learning by perusing research papers, tracking industry blogs, and participating in conferences or workshops.
- Connect with the AI community via online forums, social media, and networking events. Collaborating and sharing knowledge can boost your learning and keep you inspired.
7. Secure Industry Experience:
- Seek internships, co-op programs, or entry-level roles in organizations or research institutions involved in AI-related projects.
- Forge relationships with professionals in the field through networking events, LinkedIn, and other professional platforms.
8. Specialize and Progress:
- As you gather experience, think about focusing on a specific AI area such as computer vision, natural language processing, robotics, or reinforcement learning.
- Keep enhancing your skills and knowledge through online courses, certifications, or advanced degrees to remain competitive.
By adhering to these steps and constantly learning and adapting to emerging technologies and methods, you can shape a thriving career as an AI engineer.
1. Lay the Educational Groundwork:
- Bachelor's Degree: Kick-off your journey with a bachelor's degree in a relevant field like computer science, mathematics, statistics, or engineering. Prioritize courses in artificial intelligence, machine learning, data science, computer programming, and algorithms.
- Master's Degree (Optional): If you're keen on advanced research or specialized applications, a master's degree in artificial intelligence, machine learning, or a related field can be a valuable addition.
2. Acquire Programming Skills:
- Familiarize yourself with programming languages frequently used in AI development, such as Python, R, and Java. Python is a favorite choice due to its vast libraries for AI and data science, including TensorFlow, PyTorch, and scikit-learn.
3. Become Proficient in Machine Learning and Deep Learning:
- Grasp the basics of machine learning algorithms, techniques, and methodologies. Get a handle on supervised learning, unsupervised learning, reinforcement learning, and deep learning.
- Delve into neural networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and other deep learning structures.
4. Build a Solid Mathematical Foundation:
- Enhance your mathematical skills, especially in linear algebra, calculus, probability, and statistics. These principles are crucial for understanding the mechanics of machine learning algorithms.
5. Engage in Projects:
- Get hands-on experience by undertaking AI projects. This could include crafting machine learning models, developing AI applications, or competing in Kaggle contests.
- Construct a portfolio to display your projects and exhibit your abilities to prospective employers or partners.
6. Stay Informed and Connect with the Community:
- Keep abreast of the latest trends in AI and machine learning by perusing research papers, tracking industry blogs, and participating in conferences or workshops.
- Connect with the AI community via online forums, social media, and networking events. Collaborating and sharing knowledge can boost your learning and keep you inspired.
7. Secure Industry Experience:
- Seek internships, co-op programs, or entry-level roles in organizations or research institutions involved in AI-related projects.
- Forge relationships with professionals in the field through networking events, LinkedIn, and other professional platforms.
8. Specialize and Progress:
- As you gather experience, think about focusing on a specific AI area such as computer vision, natural language processing, robotics, or reinforcement learning.
- Keep enhancing your skills and knowledge through online courses, certifications, or advanced degrees to remain competitive.
By adhering to these steps and constantly learning and adapting to emerging technologies and methods, you can shape a thriving career as an AI engineer.
Jaquan Outlaw
Data Scientist
27
Answers
Tampa, Florida
Updated
Jaquan’s Answer
Becoming an AI Engineer involves a combination of obtaining a solid academic background, gaining practical experience, and staying updated with the latest trends and technologies in the field. Here are some steps to guide you:
1. Obtain a Bachelor's Degree
Getting a bachelor's degree in a relevant field like Computer Science, Data Science, Mathematics, or Information Technology can be a good start. These programs offer foundational knowledge in algorithms, data structures, and programming languages.
2. Gain Proficiency in Programming Languages
Python is widely used in AI and machine learning due to its simplicity and robust libraries. Other useful languages include Java, C++, and R. Familiarity with these languages aids in implementing AI models.
3. Learn AI and Machine Learning Concepts
Master the fundamentals of AI and machine learning. This includes understanding various algorithms, neural networks, deep learning, reinforcement learning, natural language processing, etc. Online platforms like Coursera, edX, and Udacity offer courses in these areas.
4. Get Hands-on Experience
Practical application of AI concepts is crucial. Work on projects, whether personal, academic, or through internships, to gain experience. Participate in coding competitions or contribute to open-source projects. Platforms like Kaggle provide datasets to work on real-world problems.
5. Pursue a Master's Degree or Specialized Certification (Optional)
While not always necessary, a master's degree or a certification in AI or machine learning can provide more specialized knowledge and make you more competitive in the job market.
6. Stay Updated
AI is a rapidly evolving field. Keep learning and stay updated with the latest advancements and trends. Engage with AI communities, attend seminars/webinars, and follow relevant publications.
7. Develop Soft Skills
In addition to technical skills, develop soft skills like problem-solving, critical thinking, communication, and teamwork. These are valuable in any professional setting.
Remember, the journey to becoming an AI engineer requires continuous learning and practice. It's a challenging field, but also one with immense potential and opportunities.
1. Obtain a Bachelor's Degree
Getting a bachelor's degree in a relevant field like Computer Science, Data Science, Mathematics, or Information Technology can be a good start. These programs offer foundational knowledge in algorithms, data structures, and programming languages.
2. Gain Proficiency in Programming Languages
Python is widely used in AI and machine learning due to its simplicity and robust libraries. Other useful languages include Java, C++, and R. Familiarity with these languages aids in implementing AI models.
3. Learn AI and Machine Learning Concepts
Master the fundamentals of AI and machine learning. This includes understanding various algorithms, neural networks, deep learning, reinforcement learning, natural language processing, etc. Online platforms like Coursera, edX, and Udacity offer courses in these areas.
4. Get Hands-on Experience
Practical application of AI concepts is crucial. Work on projects, whether personal, academic, or through internships, to gain experience. Participate in coding competitions or contribute to open-source projects. Platforms like Kaggle provide datasets to work on real-world problems.
5. Pursue a Master's Degree or Specialized Certification (Optional)
While not always necessary, a master's degree or a certification in AI or machine learning can provide more specialized knowledge and make you more competitive in the job market.
6. Stay Updated
AI is a rapidly evolving field. Keep learning and stay updated with the latest advancements and trends. Engage with AI communities, attend seminars/webinars, and follow relevant publications.
7. Develop Soft Skills
In addition to technical skills, develop soft skills like problem-solving, critical thinking, communication, and teamwork. These are valuable in any professional setting.
Remember, the journey to becoming an AI engineer requires continuous learning and practice. It's a challenging field, but also one with immense potential and opportunities.
Karin P.
Lecturer
375
Answers
Durban, KwaZulu-Natal, South Africa
Updated
Karin’s Answer
Hi Muhammed,
It's amazing and wonderful how many skills you have already developed. Keep that up and get some "real-world" experience doing internships or maybe freelancing. Document your projects in a portfolio too.
In order to progress towards being an AI engineer, I would recommend doing a bachelors in computer science, data science, statistics or information technology. You could then do your masters specializing in AI or possibly go to industry directly if you wish.
You could also combine the mathematical/data part with another discipline like e.g. physics, meteorology or materials science going towards physics-informed machine learning. This approach bridges the gap between purely data-driven and first-principles driven modelling for more accurate and physically meaningful predictions. The applications are huge. I have attached a link for you below.
I hope this helps! Enjoy the ride!
KP
https://www.pnnl.gov/explainer-articles/physics-informed-machine-learning
It's amazing and wonderful how many skills you have already developed. Keep that up and get some "real-world" experience doing internships or maybe freelancing. Document your projects in a portfolio too.
In order to progress towards being an AI engineer, I would recommend doing a bachelors in computer science, data science, statistics or information technology. You could then do your masters specializing in AI or possibly go to industry directly if you wish.
You could also combine the mathematical/data part with another discipline like e.g. physics, meteorology or materials science going towards physics-informed machine learning. This approach bridges the gap between purely data-driven and first-principles driven modelling for more accurate and physically meaningful predictions. The applications are huge. I have attached a link for you below.
I hope this helps! Enjoy the ride!
KP
Karin recommends the following next steps:
Mikaela Dorch
Digital Media Artist & Creative Strategist
1
Answer
California, California
Updated
Mikaela’s Answer
Hello Muhammad!
I hope this message finds you well, and I appreciate your strong passion for art and technology! Since your creative and technical backgrounds are in coding, 3D modeling, AI, and VR mediums, I highly recommend you major in computer science, and digital/new media arts as a double major or minor in your college programs.
By majoring in computer science, you will learn plenty of new coding languages, software, and methods of machine learning that will apply to your ultimate goal as an AI engineer. In addition, you will also gain collaborative skill sets with other programmers in this major to help you stay on top of new cutting-edge technology emerging in the AI and VR field.
I also suggest double majoring or minoring in digital/new media arts. This program offers so many new technical and creative ways to combine art & technology in various mediums (i.e. creative coding, video game design, 3D modeling & print, VR/AR projects, and more). Having a background in digital/new media art will help you stand out against the competitive crowd of AI engineering if you are looking more toward real-time interactive projects and creative job positions.
During your studies, I recommend you find part-time/internship jobs related to software engineering and product design roles. This will help you build experience and case studies to show future employers or for personal endeavors in the AI field. Also, experiment with new AI startup software to gain more familiarity with the emerging field and to build connections with other entry to mid-level software engineers and designers.
I hope this advice helps, and I wish you luck in your education and career endeavors! If you have any more questions, please let me know. I am a recent San Jose State University digital media art graduate who has worked on projects with computer science majors.
Best regards,
Mikaela D.
I hope this message finds you well, and I appreciate your strong passion for art and technology! Since your creative and technical backgrounds are in coding, 3D modeling, AI, and VR mediums, I highly recommend you major in computer science, and digital/new media arts as a double major or minor in your college programs.
By majoring in computer science, you will learn plenty of new coding languages, software, and methods of machine learning that will apply to your ultimate goal as an AI engineer. In addition, you will also gain collaborative skill sets with other programmers in this major to help you stay on top of new cutting-edge technology emerging in the AI and VR field.
I also suggest double majoring or minoring in digital/new media arts. This program offers so many new technical and creative ways to combine art & technology in various mediums (i.e. creative coding, video game design, 3D modeling & print, VR/AR projects, and more). Having a background in digital/new media art will help you stand out against the competitive crowd of AI engineering if you are looking more toward real-time interactive projects and creative job positions.
During your studies, I recommend you find part-time/internship jobs related to software engineering and product design roles. This will help you build experience and case studies to show future employers or for personal endeavors in the AI field. Also, experiment with new AI startup software to gain more familiarity with the emerging field and to build connections with other entry to mid-level software engineers and designers.
I hope this advice helps, and I wish you luck in your education and career endeavors! If you have any more questions, please let me know. I am a recent San Jose State University digital media art graduate who has worked on projects with computer science majors.
Best regards,
Mikaela D.
Thank you so much Mikaela
Muhammed
Latest Keygen
Blogging
1
Answer
Lahore, Punjab, Pakistan
Updated
Latest’s Answer
In short, the best route to becoming an AI engineer involves:
Obtaining a degree in computer science or a related field.
Learning programming languages such as Python and mastering AI concepts through online courses and projects.
Gaining practical experience through internships, entry-level positions, and personal projects.
Continuously updating skills and staying abreast of advancements in AI technology.
Visit this site https://latestkeygen.com/affinity-photo-free-crack/
Obtaining a degree in computer science or a related field.
Learning programming languages such as Python and mastering AI concepts through online courses and projects.
Gaining practical experience through internships, entry-level positions, and personal projects.
Continuously updating skills and staying abreast of advancements in AI technology.
Visit this site https://latestkeygen.com/affinity-photo-free-crack/