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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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6 Topics

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Lesson time ~ 10 hours

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00:00

ML Engineer

MACHINE LEARNING ENGINEER

ROLE OVERVIEW

A Machine Learning Engineer specializes in developing systems and algorithms that enable machines to learn and make predictions or decisions without being explicitly programmed for each task. This role sits at the intersection of computer science and data science and is pivotal in designing and implementing artificial intelligence (AI) systems that can process and learn from large sets of data.

KEY RESPONSIBILITIES

  • Design and Develop Machine Learning Systems: Machine Learning Engineers are responsible for designing, developing, and researching machine learning systems and models. This involves selecting appropriate datasets, choosing suitable data representation methods, and identifying differences in data distribution that could affect model performance[1][4][18].

  • Implement Machine Learning Algorithms: They implement machine learning algorithms and run AI systems experiments and tests. This includes performing statistical analyses and using the results to improve models[20].

  • Optimize ML Systems and Algorithms: Part of their job is to optimize machine learning systems and algorithms for better efficiency and accuracy. This includes training and retraining systems as needed and extending machine learning libraries[18].

  • Collaboration: Machine Learning Engineers often work as part of a larger data science team, collaborating with data scientists, software engineers, and product managers. They act as a bridge between the theoretical models developed by data scientists and the practical implementation of these models in production systems[18].

EDUCATION AND SKILLS

  • Advanced Degree: Most machine learning job descriptions require at least a Master’s degree in computer science, mathematics, statistics, or related fields. There are almost as many listings asking for a Ph.D. as those looking for a Master’s degree[11].

  • Programming Skills: Proficiency in programming languages such as Python, Java, C++, and R is essential. Familiarity with machine learning frameworks like TensorFlow or Keras and libraries such as scikit-learn is also crucial[1][18].

  • Math and Statistics Knowledge: Advanced knowledge in mathematics and statistics, particularly in areas like calculus, linear algebra, and Bayesian statistics, is necessary for understanding and implementing machine learning algorithms[18].

  • Software Engineering Skills: Experience with software engineering and familiarity with tools and technologies used in developing and deploying machine learning models are important[20].

HOW TO BECOME ...

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

  • Obtain a Relevant Degree: Start with a bachelor’s degree in computer science, data science, or a related field. Focus on courses that cover AI, machine learning, statistics, and programming[3][6].
  • Pursue Advanced Education: Consider pursuing a Master’s or Ph.D. in fields like artificial intelligence, machine learning, or computer science to gain deeper knowledge and specialize in AI[3][6].
  • Gain Practical Experience: Work on real-world projects, participate in hackathons, and contribute to open-source projects to apply your knowledge and build a portfolio. Internships or entry-level jobs in machine learning or data science can provide valuable experience[2][6].
  • Earn Certifications: Certifications from reputable organizations or technology providers can enhance your skills and demonstrate your expertise in AI and machine learning[6][12].
  • Stay Updated and Network: AI and machine learning are rapidly evolving fields. Stay updated with the latest developments, participate in online communities, and network with professionals in the field to learn about new opportunities and trends[6][9].

In summary, a Machine Learning Engineer is a key player in developing intelligent systems that can learn from data. The role requires a strong foundation in computer science, mathematics, and programming, along with practical experience and continuous learning to keep up with the advancements in the field.

FREE COurses

Here’s a list of free Machine Learning (ML) Engineer online courses, as mentioned in the provided sources:

5 Free Courses to Master Machine Learning – KDnuggets

  • Machine Learning for Everybody: Taught by Kylie Ying, this course adopts a code-first approach to building machine learning models in Google Colab, covering topics from K-Nearest Neighbors to Principal Component Analysis (PCA).
  • Kaggle Machine Learning Courses: Offers a series of micro-courses covering the fundamentals of machine learning, including Intro to Machine Learning and Intermediate Machine Learning, with practical exercises.

Top Free Machine Learning Courses & Tutorials Online – Udemy

  • Udemy lists various free machine learning courses, although specific courses are not detailed in the source, Udemy is known for offering a wide range of topics including Python for Machine Learning & Data Science.

Top 9 Free Machine Learning Courses To Fast-Track Your Career – Simplilearn

  • Machine Learning Basics: A course that provides a solid foundation in machine learning, covering data preprocessing, time series modeling, text mining, and supervised and unsupervised learning.
  • Introduction to Artificial Intelligence Course: Covers the basics of AI alongside machine learning and deep learning, focusing on use cases and the differences between supervised, unsupervised, and reinforcement learning.

Machine Learning Courses and Certifications – Class Central

  • Class Central lists free and free-to-audit online courses from top universities like Harvard, Stanford, MIT, and the University of Pennsylvania, covering a broad range of machine learning topics.

Top 10+ Free Machine Learning And Artificial Intelligence Courses In 2024 – DLabs.AI

  • Machine Learning Introduction for Everyone: A beginner-friendly course from IBM that takes about seven hours to complete, covering the basics of machine learning, supervised and unsupervised learning, and ML tools and applications.
  • Machine Learning for Data Science and Analytics: Offered by Columbia University, this course focuses on the fundamentals of ML and its algorithms, including linear regression and supervised and unsupervised learning.

Best Machine Learning Courses Online [2024] – Coursera

  • Coursera offers machine learning courses from top-ranked colleges like the University of Illinois, Imperial College London, and the University of Michigan, covering a wide range of ML topics.

Best Online Machine Learning Courses and Programs – edX

  • edX provides machine learning courses that explore topics like data science, data mining, statistical learning, and pattern discovery, with real-life applications such as spam filtering and facial recognition.

70+ FREE AI & ML Courses!! – LinkedIn

  • This LinkedIn article lists over 70 free AI and ML courses, including offerings from Stanford University, University of London, Georgia Tech, and various courses on Udacity and Coursera tailored for beginners to advanced learners.

These courses offer a great starting point for anyone looking to enter the field of machine learning engineering, providing both theoretical knowledge and practical skills.

UNIVERSITIES COurses & CERTIFICATIONS

Here’s a list of machine learning certifications offered by universities, as mentioned in the provided sources:

Cornell University – Machine Learning Certificate Program

Offered by eCornell, Cornell University’s online learning platform, this program equips participants to implement machine learning algorithms using Python. It covers a range of topics from basic computations and linear algebra to advanced machine learning techniques such as Maximum Likelihood Estimate (MLE), Naive Bayes Classifier, and decision trees[1].

University of Washington – Certificate in Machine Learning

The University of Washington provides a certificate program in machine learning through its Professional & Continuing Education department. The program includes courses on Introduction to Machine Learning, Advanced Machine Learning, and Deep Learning. It is designed to be flexible with evening and online classes[2].

Stanford University – Machine Learning Certification

Offered through Coursera, this certification provides a broad introduction to machine learning, data mining, and statistical pattern recognition. The course is taught by Andrew Ng, a co-founder of Coursera and a professor at Stanford University. Topics include supervised learning, unsupervised learning, best practices in machine learning, and more[3].

Harvard University – Professional Certificate in Data Science

This certification is part of a broader data science program offered by Harvard University via edX. It allows candidates to earn a machine learning certificate without completing the entire Professional Certificate in Data Science. The program covers key machine learning algorithms and provides hands-on experience[3][4].

MIT Professional Education – Professional Certificate Program in Machine Learning & Artificial Intelligence

MIT Professional Education offers this certificate program, guiding participants through the latest advancements and technical approaches in AI technologies such as natural language processing, predictive analytics, deep learning, and algorithmic methods. The program aims to further participants’ knowledge of the ever-evolving AI industry[5].

These certifications from prestigious universities cover a wide range of machine learning topics and provide a solid foundation for anyone looking to advance their career in this field.

 

SALARY INFO

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

Source Average Annual Salary Salary Range
Indeed $162,806 Not specified
Glassdoor $156,110 Not specified
Built In $155,888 $44,000 – $170,000
Coursera $116,416 – $140,180 Not specified
ZipRecruiter Not specified by state Not specified by state
Salary.com $105,183 $96,146 – $114,777
Talent.com $160,456 $130,000+
neptune.ai Entry: ~$97,090 Mid: $112,095 Senior: $132,500 Entry: Up to $130,000+ Mid: Up to $160,000+ Senior: Up to $181,000

The salary ranges for an Machine Learning Engineer can vary widely based on factors such as location, experience, industry, and the specific company. The table above provides a snapshot of the salary expectations from different sources, but it’s important to note that these figures are subject to change and may differ based on individual circumstances.

 

LEARNING VIDEOS

11:34min.

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
[2] https://www.bestcolleges.com
[3] https://www.simplilearn.com/tutorials/artificial-intelligence-tutorial/how-to-become-an-ai-engineer
[4] https://www.toptal.com/machine-learning/job-description
[5] https://www.wgu.edu/career-guide/information-technology/machine-learning-engineer-career.html
[6] https://www.coursera.org/articles/ai-engineer
[7] https://www.reddit.com/r/MachineLearning/comments/17hwwf0/d_what_are_your_duties_as_a_machine_learning/
[8] https://engineeringonline.ucr.edu/blog/how-to-become-a-machine-learning-engineer/
[9] https://www.reddit.com/r/MLQuestions/comments/10203t1/how_to_become_a_aiml_engineer/
[10] https://brainstation.io/career-guides/what-is-a-machine-learning-engineer
[11] https://365datascience.com/career-advice/career-guides/machine-learning-engineer/
[12] https://learn.microsoft.com/en-us/training/career-paths/ai-engineer
[13] https://emeritus.org/in/learn/what-are-the-roles-and-responsibilities-of-a-machine-learning-engineer/
[14] https://www.indeed.com/career-advice/finding-a-job/how-to-become-machine-learning-engineer
[15] https://news.ycombinator.com/item?id=36432598
[16] https://www.indeed.com/hire/job-description/machine-learning-engineer
[17] https://vault.com/professions/machine-learning-engineers/requirements
[18] https://www.techtarget.com/searchenterpriseai/definition/machine-learning-engineer-ML-engineer
[19] https://career-bootcamp.extension.ucsd.edu/blog/machine-learning-engineering/how-to-become-a-machine-learning-engineer/
[20] https://www.coursera.org/articles/what-is-machine-learning-engineer

Courses and Certifications
[1] https://ecornell.cornell.edu/certificates/technology/machine-learning/
[2] https://www.pce.uw.edu/certificates/machine-learning
[3] https://www.springboard.com/blog/data-science/machine-learning-certificates/
[4] https://www.projectpro.io/article/machine-learning-certifications/878
[5] https://professional.mit.edu/course-catalog/professional-certificate-program-machine-learning-artificial-intelligence-0
[6] https://hackr.io/blog/machine-learning-certifications 
[7] https://www.datacamp.com/blog/top-machine-learning-certifications
[8] https://digitaldefynd.com/7-best-machine-learning-training-certifications/

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