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🌟 AI Career Master Class

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  1. 1 - THE ULTIMATE AI CAREER COURSE

    1.1 Welcome to "Master Your Career with AI"
    4 Topics
  2. 1.2 Launch Your Path to Success
    2 Topics
  3. 1.3 What is AI and Why it Will Change Everything
    5 Topics
  4. 1.4 Your Feedback
  5. 2 - AI CAN HELP YOU IN YOUR CAREER
    2.1 Most Important Career Activities you Need to Master
    10 Topics
    |
    10 Quizzes
  6. 2.2 How AI can Become Your Superpower
    2 Topics
  7. 2.3 Your Feedback
  8. 3 - TOP GENERATIVE AI TOOLS YOU NEED TO KNOW
    3.1 These 5 Gen AI Tools You Need To Master
    5 Topics
  9. 3.2 AI Writing Tools Which Are Magic
    6 Topics
  10. 3.3 AI Voice Tools Which Listen To You
    3 Topics
  11. 3.4 Learn These Mind Blowing AI Art Tools
    6 Topics
  12. 3.5 These AI Video Generator Are Game Changer
    6 Topics
  13. 3.6 Your Feedback
  14. 4 - AI'S INFLUENCE ON THE FUTURE OF WORK
    4.1 AI Solutions Shaping Industries
    8 Topics
  15. 4.2 How AI Is Transforming Jobs
    8 Topics
  16. 4.3 New AI Jobs and Opportunities
    10 Topics
  17. 4.3 Your Feedback
  18. 5 - LEARN TO PROMPT PERFECT (ACCESS TO 100+ PROMPT LIBRARIES)
    5.1 Learn to Use AI for Your Benefit
    3 Topics
  19. 5.2 Your Feedback
  20. 6 - The POWER OF CERTIFICATES (ACCESS TO 100+ Certificates)
    6.1 Get Yourself a Certificate
    2 Topics
  21. 6.2 Your Feedback
  22. 7 - WHERE TO FIND AI JOP OPENINGS? (ACCESS TO 100+ AI Job Openings)
    7.1 AI Job Catalogs
    6 Topics
  23. 7.2 Your Feedback
  24. 8 - USE AI TO LEVEL UP IN YOUR CURRENT ROLE
    8.1 Become an AI Expert in Your Domain
    3 Topics
  25. 8.2 How to Use AI as a Promotion Booster
    3 Topics
  26. 8.3 AI-Powered Networking
    4 Topics
  27. 8.4 Your Feedback
  28. 9 - HOW AI CAN HELP YOU GETTING A NEW/DREAM JOB
    9.1 AI To Create A Perfect Application
    6 Topics
  29. 9.2 Enhancing Interview Performance with AI Insights
  30. 9.3 Your Feedback
  31. 10 -AI ON THE WAY TO AGI - ETHICAL CONSIDERATIONS
    10.1 Ethical Questions and Considerations using AI
    6 Topics
  32. 10.2 Your Feedback
  33. 11 - AI POWERED CAREER PLANNING - NEXT SECRET TO SUCEES
    11.1 Creating a Career Plan with AI-driven Insights
    3 Topics
  34. 12 - AI Newsletters and Resources
    12.1 - Key AI Publications, Newsletter and Resources
    5 Topics
  35. 13 - Roadmap
    13.1 - Roadmap and Releases
  36. TBD Parking Lot
    Course Recap
    2 Topics
  37. Additional Resources
    1 Topic
  38. Make AI your Career Superpower
    4 Topics
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2 Videos 45 min.

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AI Engineer

Ai-Engineer

ROLE OVERVIEW

An AI Engineer is a professional who specializes in creating and implementing artificial intelligence (AI) systems. These individuals are responsible for developing algorithms and models that enable machines to perform tasks that typically require human intelligence. This includes a wide range of applications, from natural language processing and robotics to predictive analytics and computer vision.

KEY RESPONSIBILITIES

  • Developing AI Models: AI Engineers build models from scratch and help various stakeholders understand the outcomes these models will yield.

  • Statistical Analysis: They perform statistical analysis and interpret the results to guide and optimize organizational decision-making processes.

  • AI Infrastructure: They create and manage the AI product development and infrastructure, including data transformation and ingestion infrastructures.

  • Machine Learning: AI Engineers run AI and machine learning experiments and tests, train systems when necessary, and transform machine learning models into APIs for other applications to interact with.

  • Cross-functional Collaboration: They collaborate across teams to help with AI adoption and best practices, ensuring that AI tools are updated in sync with the latest developments[1][2][4][7][8][10][11][13][14][17][18].

EDUCATION AND SKILLS

  • Bachelor’s Degree: Typically, AI Engineers hold a bachelor’s degree in computer science, data science, mathematics, or a related discipline. While not always required, a master’s degree in these fields can be beneficial[14][18].

  • Technical Skills: Proficiency in programming languages such as Python, R, Java, and C++ is essential. AI Engineers must also have a strong understanding of probability, statistics, calculus, and linear algebra, as well as familiarity with big data technologies like Hadoop, Apache Spark, Cassandra, and MongoDB[2][11][14].

  • Machine Learning Knowledge: They should understand machine learning algorithms and be able to implement them using frameworks like TensorFlow, Caffe, Keras, and PyTorch[11][14].

  • Soft Skills: Effective communication, problem-solving abilities, time management, teamwork, and critical thinking are crucial for success in this role[10].

HOW TO BECOME ...

Becoming an AI Engineer involves a combination of education, practical experience, and continuous learning:

  • Educational Foundation: Obtain a degree in a related field such as computer science, data science, or mathematics. Consider pursuing a master’s degree for advanced knowledge and opportunities[14][18].

  • Technical Proficiency: Gain proficiency in relevant programming languages and mathematical concepts. Learn to use AI and machine learning frameworks effectively[2][11][14].

  • Practical Experience: Acquire hands-on experience through internships, personal projects, or contributing to open-source projects. Practical application of skills is key to understanding real-world problems[3][12][16].

  • Certifications and Courses: Enhance your skills and knowledge by completing AI-related courses and certifications offered by reputable institutions or online platforms[2][6][8].

  • Build a Portfolio: Showcase your AI/ML projects and accomplishments in a portfolio. This can include code repositories, project descriptions, and any other relevant artifacts that demonstrate your expertise[3][12].

  • Continuous Learning: Stay updated with the latest AI and machine learning advancements by reading research papers, attending conferences, and participating in online communities[3][12].

AI Engineers are in high demand across various industries due to their ability to leverage AI technologies to solve complex problems and drive innovation. As AI continues to evolve, the role of an AI Engineer will become increasingly integral to the success of businesses and organizations[1][2]

 

FREE COurses

Here’s a list of free AI Engineer online courses based on the provided sources:

Georgia Tech’s Reinforcement Learning (Udacity)

This course, offered for free on Udacity, focuses on exploring automated decision-making from a computer science perspective. It is self-paced and takes approximately four months to complete. Participants will recreate a result from a published paper on reinforcement learning. Experience with Java and a graduate-level machine-learning qualification are recommended. While there’s no official certificate awarded for completing the course, a nano degree program certificate can be earned by completing Udacity’s “Deep Reinforcement Learning” for a fee[1].

Become an AI-Powered Engineer: ChatGPT, Github Copilot (Udemy)

This Udemy course teaches students how to create high-quality code using ChatGPT and integrate it with other text editors. It also covers how to use GitHub Copilot. The course is particularly suited to developers who want to leverage AI tools for coding responsibilities and become more efficient in their coding practices. It has received positive reviews, with 56% of reviewers giving it five stars[1].

GreatLearning’s “ChatGPT for Beginners” training course

A completely free, two-hour long beginners-focused ChatGPT course. It’s one of the few beginner’s courses on the internet that includes a section on coding prompts, along with covering email prompting. There are no prerequisites needed for this course, and it has an average rating of 4.61/5[1].

University of Pennsylvania: AI for Business (Coursera)

Offered through Coursera, this specialization is taught by eight UPenn professors from the Wharton School and other professors from the university. The courses take about four months to complete and culminate in an applied learning project. Program participants complete peer-reviewed exercises to illustrate what they’ve learned about data analytics, machine learning tools, and people management. Students can earn a certificate that can be displayed on their LinkedIn profile[2].

Google: Google AI for Everyone (edX)

A beginner course offered through edX, taking about four weeks to complete with a commitment of two-to-three hours per week. Participants learn about AI and machine learning principles and real-world applications. The course is taught by Laurence Moroney, who leads AI Advocacy at Google[2].

University of California—Davis: Big Data, Artificial Intelligence, and Ethics (Coursera)

This four-week course is part of the Computational Social Science specialization through Coursera. Participants learn about big data and its limitations, the history of artificial intelligence, and research ethics. The course is taught by Martin Hilbert, a professor at UC Davis[2].

Harvard University: Introduction to Artificial Intelligence with Python (Harvard University)

A seven-week course that requires a commitment of 10 to 30 hours per week. It covers AI algorithms, game-playing engines, handwriting recognition, and machine translation. The course includes hands-on projects and lectures and is taught by David J. Malan, a renowned computer scientist and Harvard professor[2].

IBM: AI Foundations for Everyone (Coursera)

This specialization includes three courses and takes about three months to complete with a two-hour weekly commitment. Students will learn the basics of AI, its applications, and ethical concerns. The program is taught by Rav Ahuja and Antonio Cangiano, who work for IBM’s Skills Network. Participants earn a certificate upon completion[2].

These courses offer a range of topics from introductory to more specialized areas of AI and machine learning, providing valuable resources for those looking to start or advance their knowledge in AI engineering.

 

UNIVERSITIES COurses & CERTIFICATIONS

Here’s a list of AI Engineer courses and learning certifications offered by universities, as highlighted in the provided sources:

Stanford University

  • Artificial Intelligence Graduate Certificate by Stanford University School of Engineering. This graduate certificate program covers the principles and technologies that form the foundation of AI, including logic, probabilistic models, machine learning, robotics, natural language processing, and knowledge representation. Applicants must have a bachelor’s degree with a minimum 3.0 GPA, as well as college-level calculus and linear algebra. Programming experience is also required[1].
  • Artificial Intelligence Professional Program. Earn a Stanford Professional Certificate in Artificial Intelligence by completing three courses in the AI professional education program, or two courses in the AI professional education program and one course in the AI Graduate Program. This program offers graduate-level content in Machine Learning, NLP, and more[6].

Harvard University

  • Computer Science for Artificial Intelligence. This course is part of the AI certifications listed and is designed for beginners or mid-level professionals. It covers various aspects of AI and computer science fundamentals necessary for AI[4].

Massachusetts Institute of Technology (MIT)

  • Professional Certificate Program in Machine Learning & Artificial Intelligence. Designed for professionals with at least three years of professional experience, this program guides participants through the latest advancements and technical approaches in AI technologies such as natural language processing, predictive analytics, deep learning, and algorithmic methods[8].

These programs and certifications are designed to equip participants with the necessary knowledge and skills to excel in the field of AI engineering. They cover a broad range of topics, from foundational principles to advanced techniques in machine learning and artificial intelligence.

 

SALARY INFO

Here is a table summarizing the salary ranges for an AI Engineer according to the provided sources:

SourceAverage Annual SalarySalary Range
Coursera$136,620 (Bureau of Labor Statistics) $108,043 (Glassdoor)Not specified
Levels.fyi$247,200Not specified
Glassdoor$141,312$105,984 – $196,427
Glassdoor – Artificial Intelligence Engineer$151,779$116,220 – $200,548
ZipRecruiterNot specifiedNot specified by state
Leap ScholarConverted from INR: Approximately $1,774,000₹97,76,303 – ₹1,69,50,926 (Converted from INR)
Simplilearn.comOver $110,000Up to $150,000
DataCampNot specifiedNot specified
Comparably$112,500Not specified
Indeed – Machine Learning Engineer$162,806Not specified

Please note that the salary information can vary based on factors such as experience, location, and specific employer. Additionally, the salary range provided by Leap Scholar is converted from Indian Rupees (INR) to US Dollars (USD) for comparison purposes, and the exact conversion rate is not specified. The average salaries and ranges are based on the data provided in the sources at the time of their publication.

 

LEARNING VIDEOS

15 min.

Credits and a Big Thank you to
Smitha Kolan – Machine Learning Engineer

30:15 min.

Credits and a Big Thank you to codebasics

CITATION & REFERENCES

[1] https://business.linkedin.com/talent-solutions/resources/how-to-hire-guides/artificial-intelligence-engineer/job-description 
[2] https://www.techtarget.com/whatis/feature/How-to-become-an-artificial-intelligence-engineer 
[3] https://www.reddit.com/r/MLQuestions/comments/10203t1/how_to_become_a_aiml_engineer/
[4] https://www.indeed.com/career-advice/finding-a-job/ai-engineer 
[5] https://www.indeed.com/career-advice/finding-a-job/how-to-become-ai-engineer 
[6] https://learn.microsoft.com/en-us/training/career-paths/ai-engineer 
[7] https://www.turing.com/job-description/artificial-intelligence-engineers 
[8] https://www.simplilearn.com/tutorials/artificial-intelligence-tutorial/how-to-become-an-ai-engineer 
[9] https://news.ycombinator.com/item?id=36432598 
[10] https://emeritus.org/blog/ai-engineer-job-description/ 
[11] https://www.coursera.org/articles/ai-engineer 
[12] https://www.springboard.com/blog/data-science/how-to-become-an-ai-engineer/
[13] https://www.usebraintrust.com/hire/job-description/ai-engineers 
[14] https://emeritus.org/blog/ai-ml-how-to-become-an-ai-engineer/ 
[15] https://www.upwork.com/hire/artificial-intelligence-engineers/job-description/ 
[16] https://www.datacamp.com/blog/how-to-become-an-ai-engineer
[17] https://emeritus.org/in/learn/what-are-the-roles-and-responsibilities-of-an-artificial-intelligence-engineer/ 
[18] https://www.discoverdatascience.org/career-information/artificial-intelligence-engineer/
[19] https://www.datasciencetech.institute/ai-engineer-data-engineer/

Courses and Certifications
[1] https://www.techtarget.com/whatis/feature/10-top-artificial-intelligence-certifications-and-courses 
[2] https://onlinedegrees.sandiego.edu/artificial-intelligence-courses-and-certifications/ 
[3] https://www.coursera.org/professional-certificates/ai-engineer 
[4] https://www.eweek.com/artificial-intelligence/ai-certifications/ 
[5] https://www.coursera.org/courses?query=artificial+intelligence 
[6] https://online.stanford.edu/programs/artificial-intelligence-professional-program 
[7] https://www.datacamp.com/blog/top-ai-certifications 
[8] https://professional.mit.edu/course-catalog/professional-certificate-program-machine-learning-artificial-intelligence-0

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