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.
Our AI/ML research lab now offers a quick path to certification in generative AI and other modern topics relevant to new developments in the industry, as well as traditional and specialized certifications and training. All in Python. Probably the fastest and most affordable way to earn a professional, high value certification offered by one of the top leaders in the field.
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. In particular, the Generative AI certification is based on Granville’s book on Generative AI, published by Elsevier, and offered to participants at a steeply discounted price. More will be added over time. After your purchase, email me or contact me on LinkedIn to receive the project textbook, offering numerous projects to choose from, along with my own solutions (provided for convenience). Below are answers to common questions, including how to contact me.
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. In short, it is the equivalent of an honorary certificate. 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 or in the community forum.
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. And you can work on projects using your own Python environment. If you don’t have one, help is provided to get started, with different options offered (cloud or local). Installing Python is cost-free.
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. Projects resulting in publications, with credit given to the participant, include “Synthetic Data Vendor Comparison” here, “Fast NoGAN Synthesizer” here, and “Fixing a Failed Generative Adversarial Network”, 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. 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.
6. Do you have a community forum to collaborate with other participants?
Yes we do, hosted on Slack (mltechniquesworkspace.slack.com). For participants only. It allows you to connect with other professionals, share issues, ask or answer questions, access the most recent versions of the documents, in particular the project textbook with suggested solutions. The founder now provides much of his guidance, including answering questions, on this forum. Questions can be public or private.
You will be invited to join this community, when contacting Vincent Granville after your purchase. Besides email and Slack, you can also interact with the founder on LinkedIn: see his profile page here.
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.
Mulyadi Kurniawan, Data Science Engineer — Getting the GenAI certification is not easy, but it is a rewarding experience. At work, one needs to understand how to translate their business challenges and develop a real solution. This certification is a simulation of a real journey from identifying possible paths to answer the challenges to developing solutions that surface critical insights.
Shakti Chaturvedi, Lead Data Scientist — I recently earned my GenAI certification. I can honestly say that it was one of the most challenging and rewarding experiences of my career. The certification simulates a real-world journey from identifying business challenges to developing solutions that surface critical insights. I learned a lot about the different aspects of Generative-AI, machine learning and deep learning. I also learned how to translate business challenges into data science problems. This certification & learning won’t be possible without Vincent, who dedicatedly supported me in my learning. Thanks a ton for his support & guidance.
Scott Schirkofsky, Software Engineer — I’m working on another project that I should have completed by today. I would say it’s much better than my others as I continue to learn from each one making the next better. Not only do I learn more with each project, but they become more fun to do and I continue to be anxious for the next one. There is so much to learn so for now I am focusing on supervised prediction projects.
Leon Gordon, Founder and CEO of Onyx Data — I have now had a chance to review the certification and it looks like a fantastic initiative. It would be an honor to receive the certificate.
Bill Schmarzo, Dean of Big Data — This is absolutely great Vincent! I posted the certification on LinkedIn as well. I know several folks who will be very interested in this certification!
Don Tadaya, Executive Chief Data Scientist — Dr. Granville, the dedication you commit to your craft is truly something to be admired. You have an immense set of skills & have only proven to be most benevolent in providing them to the public. Thank you for the crucial contributions you provide in AI|ML|DS, especially so in expanding on Generative AI logic & code applications. If people pay close enough attention to my work, they may find some rather similar approaches that I’ve gathered from that big brain of yours. Thank you for your service to our scientific community, for your social activity & individualized promotions through offering certification courses – they have only served to augment my team’s analytic frameworks & computational designs.
Iryna Kandidatova, Product Manager — 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.