Why is it important to learn about applied machine learning?

It's important to learn about applied machine learning if you want to pursue a career in it or if you want to know how to use it in data analysis. Applied machine learning can be used to solve problems and collect insights from big data sets. When you learn machine learning fundamentals, you will be able to do predictive analysis, data analysis, and text mining. You'll be able to apply different programming languages and platforms to the data problems faced in your organization. Applied machine learning can help you pull insights and make decisions from the information that has been collecting for a long time.

What career opportunities can arise from learning applied machine learning?

Career opportunities that arise from learning applied machine learning are mostly in computer programming. Applied machine learning, also known as automatic machine learning or AutoML, involves using computer languages for data analysis of large data. Being able to create the programs to do this is important. It is also useful to understand the power and limitations of applied machine learning if you will be using reports and making decisions based on applied machine learning. More and more management information systems include aspects of applied machine learning. This makes the field more useful to those who use data in their daily work.

How can online courses on Coursera help me learn applied machine learning?

Online courses on Coursera can help you learn applied machine learning in several languages and platforms, including Python, Matlab, Google Cloud, H20 in R, and TensorFlow. Some courses cover programming languages, and others look at how machine learning is applied to decision making in specific fields. Most courses are at an intermediate level, but a few offer a beginner-level introduction to the fundamentals of applied machine learning and how to chart, plot, and mine text to make big data usable. The courses include lectures, readings, and projects so that you can apply what you learn. Some courses stand alone, and others are part of Specializations and Professional Certificates.

What are the benefits of taking an online Applied Machine Learning course?

Online Applied Machine Learning courses offer a convenient and flexible way to enhance your existing knowledge or learn new Applied Machine Learning skills. With a wide range of Applied Machine Learning classes, you can conveniently learn at your own pace to advance your Applied Machine Learning career skills.

What Applied Machine Learning courses are best for training and upskilling employees or the workforce?

When looking to enhance your workforce's skills in Applied Machine Learning, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here .

Top Applied Machine Learning Courses - Learn Applied Machine Learning Online

Applied Machine Learning Courses Online

Explore applied machine learning for practical applications. Learn to implement models using scikit-learn, TensorFlow, and real-world datasets.

DeepLearning.AI
Machine Learning
Skills you'll gain: Machine Learning, Machine Learning Algorithms, Applied Machine Learning, Algorithms, Deep Learning, Machine Learning Software, Artificial Neural Networks, Human Learning, Statistical Machine Learning, Python Programming, Regression, Mathematics, Tensorflow, Critical Thinking, Network Model, Reinforcement Learning
Build toward a degree
Beginner · Specialization · 1 - 3 Months
DeepLearning.AI
Deep Learning
Skills you'll gain: Machine Learning, Deep Learning, Artificial Neural Networks, Machine Learning Algorithms, Applied Machine Learning, Python Programming, Machine Learning Software, Network Model, Algorithms, Computer Programming, Computer Vision, Network Architecture, Natural Language Processing, Tensorflow, Human Learning, Data Analysis, Data Model, Exploratory Data Analysis, Organizational Development, Process Analysis, Strategy, Mathematics, Mathematical Theory & Analysis, Regression, Calculus
Build toward a degree
Intermediate · Specialization · 3 - 6 Months
IBM
IBM Machine Learning
Skills you'll gain: Machine Learning, Machine Learning Algorithms, Human Learning, Statistical Machine Learning, Data Analysis, Probability & Statistics, Applied Machine Learning, Algorithms, Forecasting, General Statistics, Statistical Analysis, Regression, Deep Learning, Python Programming, Machine Learning Software, Artificial Neural Networks, Exploratory Data Analysis, Feature Engineering, Correlation And Dependence, Dimensionality Reduction, Statistical Tests, Probability Distribution, Reinforcement Learning, Network Model
Build toward a degree
Intermediate · Professional Certificate · 3 - 6 Months