To verify the authenticity of a certificate, or if you need help to add your certification to your LinkedIn profile, email us at vincentg@MLtechniques.com. We are located 2428, 35th Av. North East, in Issaquah, 20 miles East of Seattle.
MLtechniques.com is a private, self-funded ML/AI research lab developing state-of-the-art open source technologies related to synthetic data, generative AI, cybersecurity, geospatial modeling, stochastic processes, chaos modeling, and AI-related statistical optimization. It was founded in 2020 by Dr. Vincent Granville, one of the top leaders in the field, former VC-funded executive, consultant to Microsoft, Visa, Wells Fargo, eBay, NBC, and author of multiple books including “Synthetic Data And Generative AI” and “Intuitive Machine Learning and Explainable AI”.
Currently we offer the following certifications:
- Certified Machine Learning Professional
- Certified Generative AI Professional
- Certified Data Visualization Professional
- Scientific Computing with Python
- Time Series and Geospatial Modeling
- Statistical Optimization for AI and Machine Learning
- Certified NLP Professional
These topics correspond to the textbooks currently available. More will be added over time. Below are answers to common questions.
1. What are the requirements to become certified?
College-educated professionals with 2+ years of experience in any quantitative field or fluent in analyzing data, and proven experience related to the certification applied for, are automatically qualified. The verification process is based on your LinkedIn profile. A college degree may be substituted by courses from a respected provider (for instance Coursera) and/or your GitHub portfolio. Typically, busy professionals fit in this category. They can get certified in less than 24 hours without passing exams or working on projects. If you don’t meet these requirements, see next question.
2. What if I don’t meet the requirements?
We provide the training material, including relevant books, data, and notebooks. It is included in the cost discussed in question 4. You will be asked to work on two projects, create a GitHub repository if you don’t have one yet, and publish your results, including Python code and findings, on GitHub. Dr. Granville will be available to help you succeed, and provide customized assistance via email.
You need some programming experience in a language such as Python, to complete the projects in a timely fashion. No advanced calculus or statistical theory is needed as a prerequisite. No test or exam either. You are also free to seek external help to complete the projects: we actually provide useful, free external resources to candidates in addition to our own.
3. Can I see samples of training material and projects?
Jupyter notebooks, free textbook chapters, tables of contents, and Python code related to the projects, can be found on GitHub, here. For instance, the notebook on GAN (generative adversarial networks, for the Generative AI certificate) is located here. See also free training material on our company website, here.
4. What are the costs? What will I gain?
The cost is $44 per certification except Generative AI which is $63. It is a one-time cost, unlike some other providers charging a monthly fee. Despite being more affordable than any other program, the standard is high and the training material is up-to-date, enterprise-grade, and practical. In less than 30 days, you will be able to use efficient and advanced techniques on real world data, learn trade secrets from a top expert, know the limits of each method, how to overcome them, and what works best in specific contexts. No other course, even 6-month long and far more expensive, comes close to this.
The reasons for the low price is the absence of overhead costs such as office space, no overpaid administrators, training offered directly by the founder, the scalability of this program, and no advertising: we use word-of-mouth and our large internal network.
5. Can I become certified for free?
If you display the #opentowork badge on your LinkedIn profile page and meet the requirements stated in question 1 for automated qualification, you don’t need to purchase the relevant textbook. In short, there is no cost in that case. If you are currently employed, you may ask your employer to pay for your certification, or refund the expense.
6. How do I get started?
You need to purchase the relevant high quality, well organized textbook, on our e-Store, here. Textbooks are available in PDF format and contain original state-of-the-art material, numerous resources accessible in one click, illustrations, exercises, use cases and Python code. You can read and navigate them on any browser such as Chrome, Edge or Firefox. The recommended book is “Intuitive Machine Learning and Explainable AI”. For the Generative AI certificate, you must buy the book on synthetic data.
Once you completed your purchase, email us at vincentg@MLtechniques.com, mentioning your desired certification. If you automatically qualify, we will issue and email you the certificate within 24 hours, ready to post on your LinkedIn profile. If not, you will be assigned 2 projects to complete within 60 days at your own pace, and instructions to get started. You will receive email assistance directly from Dr. Granville to help you succeed and get the best value out of the program. Even if you automatically qualify, you can still choose to work on the 2 projects under our guidance. There is no extra costs.
7. How long does it take to become certified?
If you are automatically qualified, less than 24 hours (the time for us to review your profile). If not, you have up to 60 days to complete the 2 projects. Each project should take a maximum of 10 hours of work. Add to that 10 hours to learn the required material, and a small amount of time communicating with us and summarizing / posting the results. This assumes that you are familiar with Python.
8. Do you issue certificates and how to add them on my profile?
Yes we do. We will email you a customized link. When clicking on it, it will automatically add your certification to your LinkedIn profile with the correct authentication ID, verifiable by hiring managers. We will also email you step-by-step instructions to do it manually if you have difficulties: the process is straightforward and takes less than 5 minutes. For a real-life illustration, see here.
9. Is there an expiration date on the certification?
There is no expiration date on the certification. Instead, it shows when it was issued. You can always purchase it again a few years later if you want to show a more recent time stamp attached to it. You would still need to meet all the requirements to be renewed.
New textbooks or training material may be added in the future, to cover emerging technologies impacting the profession. So it would be a good investment to renew your certification or obtain a different one not yet available at this time, in a couple of years.
10. Do you have a refund policy?
The textbooks (PDF documents) are non-refundable. If we believe that you will not benefit from the program (for instance, you have no coding experience), we will refund your purchase and you won’t be enrolled. However, you are welcome to apply later when you have gained the minimum skills to succeed. If you are unsure about your eligibility, contact us prior to buying the textbooks.
In addition, if we have reached our quota of supervised students (receiving help from us to complete the projects), that option will be marked as “not available at this time” on this web page, to guarantee high quality guidance to all the active participants.
For automated qualification based on your present experience only, the certifications are available at all times. If you are unsure about whether you qualify automatically, email us.
11. What about testimonials?
Testimonials are available upon requests. Below is a small selection.
I’m happy to share that I’ve obtained a new certification: Synthetic Data & Generative AI. Thank you, Vincent Granville for sharing your knowledge. The course was amazing, packed with information and having various applications of synthetic data in different domains covered. — Iryna Kandidatova PhD, Product Manager
This was an intensive deep dive into artificial data generation, and it has helped me gain a deeper understanding of how to generate realistic data sets for a variety of applications. I am excited to apply what I learned to future data science and machine learning projects. Thank you to Vincent Granville for creating such a comprehensive and valuable learning experience. — Giuseppe M. Minardi, Data Scientist
Thank you Vincent, I appreciate your operational excellence and resources. You are an invaluable resource to the community! — Milan McGraw, AWS AI & Machine Learning