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.

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Free
Xi'an Jiaotong University
Lecture Series for Preventing and Controlling COVID-19
Skills you'll gain: Operating Systems, Recruitment, User Research, Mathematics, Training, Data Analysis, Computer Graphic Techniques, Business Psychology, Business Analysis, Business Development, Finance, Marketing Psychology, Design and Product, Account Management, Data Management, Experiment, Marketing, Algebra, Probability & Statistics, People Development, Management Accounting, Reinforcement Learning, Entrepreneurship, Accounting, Software Architecture, Epidemiology, Applied Mathematics, Algorithms, Leadership and Management, Risk Management, Computational Logic, Payments, Supply Chain and Logistics, Public Relations, Process Analysis, Spreadsheet Software, Software Engineering, Estimation, Machine Learning, Computer Graphics, Clinical Data Management, Bioinformatics, Business Communication, Operational Analysis, People Analysis, Persona Research, General Accounting, Human Computer Interaction, Communication, Human Resources, Statistical Analysis, Sales, Operations Research, Data Visualization, Health Care, Business Research, Research and Design, Scientific Visualization, Theoretical Computer Science, Strategy and Operations
4.5
(325 reviews)
Beginner · Course · 1-3 Months
University of Colorado Boulder
Master of Science in Data Science
Skills you'll gain: Data Visualization, Mathematics, Basic Descriptive Statistics, Data Structures, Data Warehousing, Computer Programming, Theoretical Computer Science, Business Psychology, Writing, Econometrics, General Statistics, Leadership and Management, Software Engineering, Algorithms, Security, Machine Learning, Analysis, Statistical Programming, Estimation, Programming Principles, Data Clustering Algorithms, Deep Learning, Decision Making, Probability & Statistics, Computer Graphics, Databases, SQL, Database Design, Machine Learning Algorithms, Computer Vision, Communication, Probability, Data Analysis, Artificial Neural Networks, Inference, Data Management, Calculus, Graph Theory, Human Resources, Probability Distribution
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Arizona State University
Master of Computer Science
Skills you'll gain: Software Engineering, General Statistics, Mobile Development, Programming Principles, Computer Programming, Computational Logic, Machine Learning, SQL, BlockChain, Leadership and Management, Computer Architecture, Software Testing, Data Management, Security Engineering, Calculus, Network Security, Product Design, Bayesian Network, Mathematics, Probability & Statistics, Computer Networking, Finance, Data Visualization, Theoretical Computer Science, Algorithms
Earn a degree
Degree
University of California San Diego
Mathematical Thinking in Computer Science
Skills you'll gain: Computer Programming, Python Programming, Research and Design, Spatial Analysis, Game Theory, Leadership and Management, Logic, Algorithms, Data Visualization, Computer Programming Tools, Programming Principles, Theoretical Computer Science, Problem Solving, Mathematics, Mathematical Theory & Analysis, Statistical Programming
4.4
(2k reviews)
Beginner · Course · 1-3 Months
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Searches related to applied machine learning

applied machine learning in python

introduction to applied machine learning

In summary, here are 10 of our most popular applied machine learning courses

Introduction to C++ Programming: Build a Calculator: Coursera Project Network
Lecture Series for Preventing and Controlling COVID-19: Xi'an Jiaotong University
Transfer Learning for Food Classification: Coursera Project Network
Image Data Augmentation with Keras: Coursera Project Network
Master of Science in Data Science: University of Colorado Boulder
Master of Computer Science: Arizona State University
Data Science Graduate Certificate: University of Colorado Boulder
Deep Learning for Healthcare: University of Illinois at Urbana-Champaign
Digital Health: Imperial College London
Mathematical Thinking in Computer Science: University of California San Diego

Skills you can learn in Machine Learning

Python Programming (33)

Tensorflow (32)

Deep Learning (30)

Artificial Neural Network (24)

Big Data (18)

Statistical Classification (17)

Reinforcement Learning (13)

Algebra (10)

Bayesian (10)

Linear Algebra (10)

Linear Regression (9)

Numpy (9)

Frequently Asked Questions 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.‎
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.‎
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.‎

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

Filter by

265 results for "applied machine learning"

Introduction to C++ Programming: Build a Calculator

Lecture Series for Preventing and Controlling COVID-19

Transfer Learning for Food Classification

Image Data Augmentation with Keras

Master of Science in Data Science

Master of Computer Science

Data Science Graduate Certificate

Deep Learning for Healthcare

Digital Health

Mathematical Thinking in Computer Science

Causal Inference

Health Data Science Foundation

Searches related to applied machine learning

In summary, here are 10 of our most popular applied machine learning courses

Skills you can learn in Machine Learning

Frequently Asked Questions about Applied Machine Learning

Why is it important to learn about applied machine learning?‎

What career opportunities can arise from learning applied machine learning?‎

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

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Filter by

265 results for "applied machine learning"

Searches related to applied machine learning

In summary, here are 10 of our most popular applied machine learning courses

Skills you can learn in Machine Learning

Frequently Asked Questions about Applied Machine Learning

Why is it important to learn about applied machine learning?‎

What career opportunities can arise from learning applied machine learning?‎

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

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