Upcoming Bootcamps
Back to Bootcamps ScheduleExplore Machine Learning
Location: Online
This two day course takes a pragmatic approach to machine learning by focusing on practical examples in order to accomplish specific goals. Students will explore different techniques, tools and frameworks while simultaneously building proper mental models to use when tackling machine learning problems.
- $1,000.00 excl.
Overview
Interest by developers and investors in machine learning is growing at an incredible rate. In 2022, it is estimated that the machine learning market was valued at $21 billion. By 2029, that number is expected to be over $200 billion!While the field is exciting and vast, it is heavily driven by complex academic research that is filled with PhD level mathematics, unapproachable equations, and a seemingly never endingvocabulary of confusing new terms. At times it can feel that those in the machine learning field intentionally want to keep the club exclusive! To say that the learning curve can be prohibitively steep would be an understatement.
This two day course takes a pragmatic approach to machine learning by focusing on practical examples in order to accomplish specific goals. Students will explore different techniques, tools and frameworks while simultaneously building proper mental models to use when tackling machine learning problems. No previous experience with machine learning or complex math is assumed or expected. Upon completion of the course, students will have built a solid foundation, allowing them to confidently venture out into the great wide world of machine learning.
Syllabus
- Define what machine learning is and the types of problems that it is good at solving
- Learn what factors should be considered when incorporating machine learning into an existing software project
- Explore platform APIs and frameworks to solve common machine learning problems
- Explore machine learning web service offerings and learn how to incorporate them
- Explore prebuilt models and learn how to integrate them
- Learn about data collection and key factors to consider
- Gain experience collecting and manually labeling data
- Learn about the power of transfer learning, and use it to build various models including object detection
- Learn python programming fundamentals necessary for machine learning
- Gain experience with and an appreciation for web-based tools such Jupyter Notebooks
- Gain exposure to core python libraries used by data scientists—NumPy, pandas and Matplotlib
- Gain a basic understanding of a neural network and gain experience building one using modern frameworks
- Receive guidance on where to go from here
Prerequisites
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It is recommended that students are already familiar with basic programming concepts: variables, statements, functions, arrays, data structures and common programming problems.
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All course exercises will be done via cloud services.Prior to the first day of class, the list of services will be provided, and accounts must be created. (All services will have free options, which will be sufficient.)
Who Should Take This Course
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Developers of all levels and backgrounds who are eager to dive into machine learning.
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Developer adjacent individuals, such as project managers, product owners and engineering managers, who want to gain an understanding of the power of machine learning.