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This course is for you if you want to

  • Use the right modeling strategy

    You have been in trouble finding the best approach to model your data.

  • Build data-efficient models

    Your models are not taking full advantage of all the available data.

  • Strengthen your ML skills

    Discover a whole landscape of Machine Learning tools.

Start learning today!

Learn from experts in the field, with +10y of experience in AI. Discover multiple advanced ML techniques, including practical examples from real-life projects. We will show you dozens of tips & tricks from our consulting practice to help you excel in your Data Science projects!
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Course curriculum

    1. Welcome aboard!

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    2. Additional Information

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    3. The Machine Learning Spectrum

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    4. Quiz

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    1. Introduction

    2. Ordinal Classification

    3. Evaluation Metrics

    4. Examples from our Practice

    5. Challenges and Common Mistakes

    6. Hands-on Session

    7. Quiz

    8. Feedback form

    9. Reference materials and further readings

    1. Introduction

    2. Self-supervised Learning

    3. Examples from our Practice

    4. Challenges and Common Mistakes

    5. Hands-on Session

    6. Quiz

    7. Feedback form

    8. Reference materials and further readings

    1. Introduction

    2. Semi Supervised Learning

    3. Examples from our Practice

    4. Challenges and Common Mistakes

    5. Hands-on Session

    6. Quiz

    7. Feedback form

    8. Reference materials and further readings

    1. Introduction

    2. Multiple Instance Learning

    3. Examples from our Practice

    4. Challenges and Common Mistakes

    5. Hands-on Session

    6. Quiz

    7. Reference materials and further readings

    8. Feedback form

    1. Introduction

    2. Multitask Learning

    3. Examples from our Practice

    4. Challenges and Common Mistakes

    5. Hands-on Session

    6. Quiz

    7. Feedback form

    8. Reference materials and further readings

About this course

  • $47.00
  • 46 lessons
  • 5.5 hours of video content
  • +25 ML techniques
  • 5 code tutorials

Gain Access to:

  • A framework to understand and recognize the top 5 Machine Learning paradigms.

  • +30 advanced Machine Learning methods. So, you will recognize the best strategy to use in your next project.

  • Discussions of real-life use cases, tips & tricks from our consulting practice using these techniques.

  • Practical code tutorials on each Machine Learning paradigm.

Meet your Instructors

Kelwin Fernandes and Paulo Maia

Kelwin is the co-founder and CEO of NILG.AI, he holds a Ph.D. in Machine Learning. Paulo is a Data Scientist at NILG.AI with a Bioengineering major. He is part of the lead team of Data Science for Social Good Portugal. Together, they have helped dozens of companies to introduce Machine Learning into their daily operations.
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Money-back guarantee

You get a deep dive into the learning strategies that allow us to excel in our consulting projects in Artificial Intelligence.

You get full access for a one-time payment. If after taking this course, you don’t feel that the content is worth at least the price you pay, e-mail us ([email protected]) within 14 days of enrollment and we’ll refund your full price.
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Thank You

FAQ

  • Who is this course for?

    This course was built considering junior to senior Data Scientists and Machine Learning practitioners that want to broaden their knowledge to more ML areas.

  • Is this an Introductory course to Machine Learning?

    No, it isn't. We assume you already have an introductory knowledge of the following concepts: supervised learning (classification and regression) and unsupervised learning (clustering). We also make reference to some deep learning concepts but we don't believe it's a major blocker to understand the overall scope of the course.

  • Do I need a deep understanding of maths and theory in Machine Learning?

    No, you don't. The course is presented in a format that should be accessible to anyone with limited fluency in maths. The goal of this course is to raise your awareness to these techniques and when to use them. For a more foundational knowledge, you should use research papers and books (that we will provide as references as part of the course).

  • I don't know programming. Can I do this course?

    Yes, you can. Most lessons will showcase the techniques (what they are, when and how to use them). There are five lessons that involve coding but we encompass them with videos explaining the code. Even if you don't understand code at all, we believe the theoretical component will be extremely relevant for you.

  • How long does the subscription last?

    You will have access to the platform for one year starting at your enrollment date, including all updates to the course content during this period. The referred price is a one-time fee for this period.

  • Do you provide corporate training?

    Yes, we do. If you want to hold live sessions of this course for your data-related teams, send us an email to [email protected].

  • Do you provide a certificate?

    Yes, we provide a certificate of completion of the course.

  • What's the course schedule?

    You will gain full access to the course content after enrollment. The total duration of the video content is mentioned on the main page of the course. You can do it at your own pace as long as you don't surpass the subscription period (1 year).

  • Do you have a refund policy?

    Yes, we do. You have 14 days to cancel your enrollment in this course. If you don't feel you obtained enough value from what you paid, or if you just realized you didn't fulfill the requirements, just contact support and we will refund your subscription.