Cross-Skilling

Start your Machine Learning career!

Learn advanced machine learning techniques and algorithms and how to package and deploy your models to a production environment. Gain practical experience using Amazon SageMaker to deploy trained models to a web application and evaluate the performance of your models. A/B test models and learn how to update the models as you gather more data, an important skill in industry.

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Estimated Duration

5 weeks of training:

  • 4 weeks of Technical training

  • 1 week of Professional training

Qualifying for

This course is qualifying you to work as

  • Machine learning Engineer

  • Data Scientist

  • MLOps Engineer

More Details

This course will qualify you to work as:

  1. Machine learning Engineer
  2. Data Scientist
  3. MLOps Engineer

Enrolled By

June 2024

After passing this course’ assessment, you will get direct access to Udacity classroom

Prerequisites

You should meet the following criteria:

More Details
  1. Intermediate Python programming knowledge, including at least 40 hours of programming experience
  2. Familiarity with data structures like dictionaries and lists
  3. Experience with libraries like NumPy and pandas
  4. Basic knowledge of probability and statistics, including experience calculating the probability of an event
  5. Familiarity with terms like the mean and variance of a probability distribution
  6. You haven’t joined the Cross-skilling track before either for this specialization or a different one.
 
 
  • Intermediate Python programming knowledge, including at least 40 hours of programming experience

  • Familiarity with data structures like dictionaries and lists

  • Experience with libraries like NumPy and pandas

  • Basic knowledge of probability and statistics, including experience calculating the probability of an event

  • Familiarity with terms like the mean and variance of a probability distribution

  • You haven’t joined the Cross-skilling track before either for this specialization or a different one.

Provided by

Built with callaboration with

What you will learn?

As Machine Learning Engineer You will learn

The key skills demonstrated will include:

  • Supervised learning
  • Model evaluation and comparison
  • Tuning models according to constraints.

Why Agile?

Identify the importance of the Agile in the tech fields

Agile vs Traditional Management

Compare Agile versus the more traditional Waterfall approach to product development

Extra Training of

Agile Management

Agile Planning

Compare, Evaluate and Contrast Scrum, Kanban, and XP

Build and Evolve Agile Teams

Identify an Agile team’s core roles, optimal size, structure, and cross-functional skills

Enjoy our

Career Readiness Privileges

Resume Review

Get a detailed resume review from an industry professional.

LinkedIn Review

Get a customized review of your LinkedIn profile from an industry professional.

GitHub Review

A technical professional will help you organize your profile to showcase your projects and skills.

Watch our graduates’ stories!

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Why do you study with Udacity?

Job-ready talent. Superior outcomes

We partner with leading technology companies to learn how technology is transforming industries, and teach the critical tech skills that companies are looking for in their workforce. With our powerful and flexible digital education platform, even the busiest learners can prepare themselves to take on the most in-demand tech roles.

Industry Relevant Content

Certified Certificate

Real-World Projects

Students Community

Career Enablement

Mentors & Trainers