Machine Learning Scientist Career Track

Ready to become a Machine Learning Scientist? Follow our structured Machine Learning Scientist Career Track to master essential ML algorithms and techniques—from fundamental mathematics to advanced machine learning models.

10 Career Track Courses
29 Hours of Video
Certificate of Achievement
Start Your Career
Machine Learning Scientist

Machine Learning Scientist Career Track Courses

Our structured Machine Learning Scientist roadmap helps you gain the skills needed for a successful career in machine learning.

This curated machine learning curriculum offers a structured, step-by-step learning path through essential courses—from linear algebra fundamentals to advanced machine learning algorithms.

Our Machine Learning Scientist training program combines theoretical foundations with hands-on practice, preparing you for real-world ML challenges. Master key algorithms, optimize models, and select features through hands-on projects. The Machine Learning Scientist Career Track concludes with a professional certificate that validates your expertise and establishes you as a certified Machine Learning Scientist in the field.

Learn machine learning from industry experts and get certified through our comprehensive machine learning curriculum:

Linear Algebra and Feature Selection
Optional

Linear Algebra and Feature Selection

with Ivan Manov and Aleksandar Samsiev
4.7/5
(370)

Build the fundamental and practical linear algebra skills needed to become a data scientist and work on machine learning models and AI

3 hours of content
1
Math Foundation for ML
Required

Math Foundation for ML

with Neha Bansal
4.4/5
(8)

Gain a deep understanding of the core mathematical principles that power machine learning models.

1 hour of content
2
Machine Learning in Python
Required

Machine Learning in Python

with Iliya Valchanov
4.8/5
(1,574)

Master advanced statistical techniques and predictive modeling with Python. Acquire the essential skills for aspiring data scientists.

7 hours of content
3
Machine Learning with Naïve Bayes
Required

Machine Learning with Naïve Bayes

with Hristina Hristova
4.8/5
(740)

Master machine learning with Naïve Bayes: learn the theoretical foundations behind the Bayesian approach and gain practical problem-solving skills

2 hours of content
4
Machine Learning with K-Nearest Neighbors
Required

Machine Learning with K-Nearest Neighbors

with Hristina Hristova
4.8/5
(632)

Master K-Nearest Neighbors using Python’s scikit-learn library: from theoretical foundations to practical applications

2 hours of content
5
Machine Learning with Decision Trees and Random Forests
Required

Machine Learning with Decision Trees and Random Forests

with Nikola Pulev
4.8/5
(668)

Master Decision Trees and Random Forests: from theoretical foundations to practical applications

1 hour of content
6
Machine Learning with Support Vector Machines
Required

Machine Learning with Support Vector Machines

with Elitsa Kaloyanova
4.8/5
(594)

Master Support Vector Machines (SVMs): from theoretical foundations to practical applications

1 hour of content
7
The Machine Learning Process A-Z
Required

The Machine Learning Process A-Z

with Ken Jee and Jeff Li
4.8/5
(992)

Master the complete machine learning lifecycle: from problem definition to model deployment in production

6 hours of content
8
Machine Learning with Ridge and Lasso Regression
Elective

Machine Learning with Ridge and Lasso Regression

with Ivan Manov
4.8/5
(352)

Master regularization with ridge and lasso regression: from theoretical foundations to practical applications

1 hour of content
9
The Machine Learning Algorithms A-Z
Elective

The Machine Learning Algorithms A-Z

with Ken Jee and Jeff Li
4.7/5
(614)

Master the core concepts of popular ML algorithms: understand when and how to apply different machine learning techniques effectively

5 hours of content
10

Complete the Machine Learning Scientist Career Track and Get Certified

Earn your Machine Learning Scientist certificate to demonstrate your expertise to potential employers. Build a portfolio of machine learning projects showcasing your practical skills in implementing ML solutions.

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FAQs

Need help finding what you're looking for? Visit the 365 Data Science Help Center page or contact us directly.

What is the career path for machine learning?
A typical machine learning scientist’s career progression includes:
  • Junior ML Scientist: Implementation of basic ML models
  • ML Scientist: Development of complex algorithms
  • Senior ML Scientist: Leading ML research projects
  • Lead ML Scientist: Driving ML strategy
  • ML Director: Overseeing ML teams and initiatives
Each level requires increasing expertise in algorithms, research, and leadership.

Start your machine learning training today to break into this exciting career path!
How do I become a machine learning scientist?
Start your journey with essential machine learning scientist courses:
  • Mathematical foundations
  • Programming skills
  • ML algorithms
  • Practical projects
Our Machine Learning Scientist Career Track provides comprehensive training for this career path.
Can you do ML research without PhD?
Yes! While a PhD can be beneficial, many successful ML Scientists have built careers through practical experience and comprehensive machine learning scientist programs like ours.

Focus on building strong technical skills, creating a robust project portfolio, and gaining hands-on experience with real-world ML applications.
How long does it take to become a Machine Learning Scientist?
The journey to machine learning certification typically takes 3 to 6 months with dedicated study through our training program.

This timeline, however, can vary based on your background, learning pace, and prior experience with programming and mathematics.
Is a career as a Machine Learning Scientist a good choice?
Yes! A career in Machine Learning Science promises:
  • Strong job security
  • A competitive machine learning scientist’s salary around $200,000 annually
  • Continuous learning opportunities
  • Engagement with cutting-edge technology
  • Broad industry impact
Are Machine Learning Scientist jobs in demand?
The demand for machine learning scientists is exceptionally high.

According to the U.S. Bureau of Labor Statistics, the job market is expected to grow by 32% by 2033.

Companies across all sectors actively recruit ML professionals as AI and ML become increasingly crucial for innovation and operations.
How difficult is it to become a Machine Learning Scientist?
While becoming a Machine Learning Scientist requires dedication to learning complex concepts and algorithms, our structured machine learning curriculum makes this journey manageable.

We break down complex concepts, provide hands-on practice, offer expert guidance, and help you earn a machine learning certification.
What are the essentials to begin a career as a Machine Learning Scientist?
To begin your Machine Learning Scientist career path, you will need:
  • Strong mathematics foundation
  • Programming knowledge
  • Understanding of statistics
  • Willingness to learn ML algorithms
  • Commitment to completing hands-on projects
Our Machine Learning Scientist Career Track provides all the necessary training and resources to help you start your journey.

Machine Learning Scientist Career Track

10 Courses

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