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Machine Learning and Artificial Intelligence: What is the difference?

Machine Learning and Artificial Intelligence

Artificial Intelligence and Machine Learning projects are a buzz these days. Perhaps more than our daily lives, Artificial Intelligence and Machine Learning are impacting the business world like never before. ML and AI are everywhere, from setting up and maintaining complex information systems to gaming stations. And Tech giants like Facebook, Google, and Amazon are already implementing Machine Learning and Artificial Intelligence in the projects and products. But this is just the beginning. In the coming years, ML and AI are steadily making inroads into pretty much every industry.

What is Machine Learning?

Machine Learning is a form of data analysis is used to automate analytical model building. Machine Learning projects enable computers to learn from data, identify patterns and implement decisions with minimal human intervention. Machine Learning algorithms rely on historical data as input to predict anticipated output values.

Why is Machine Learning important?

Machine Learning algorithms give businesses a view of trends in customer behavior as well as business operational patterns. ML algorithms are also used for supporting product development. As already mentioned, most of today’s leading tech companies have made Machine Learning algorithms a central part of their operations.

What is Artificial Intelligence?

Artificial Intelligence (AI) is basically a system that trains machines to perform human-like tasks. At the very basic level, AI is where machines are trained to imitate human behavior such as problem-solving, learning, and planning. Artificial Intelligence enables machines to analyze data and identify patterns within it for purposes of replicating those behaviors.

Why is Artificial Intelligence Important?

The amount of data being generated today far outpaces human’s ability to absorb, comprehend, and make complex decisions using that data. Artificial Intelligence projects for the basis for computers to train and make complex decisions in the shortest time possible. AI, like Machine Learning, is increasingly finding applications in various industries such as security, health, and enterprise development.

What skills do you require to master Machine Learning and Artificial Intelligence?

Since Artificial Intelligence is a broad term for smart applications, the necessary skillset for becoming an AI expert is more theoretical than technical. Machine learning algorithms, on the other hand, require a higher level of technical expertise to master.

Skills you need to master Artificial Intelligence

It is important that you have a foundation in the following to pursue a career in Artificial Intelligence.

  • Algorithm analyzing techniques
  • Machine Learning and how to draw inference from data
  • Ethical concerns in developing appropriate AI technologies
  • Robotics
  • Data Science
  • Programming design
  • Java Programming
  • Problem Solving
  • Data Mining

Skills you need to master Machine Learning

  • It is important that you have a foundation in the following in order to pursue a career in Machine Learning:

    • Neural Networks architectures
    • Applied Mathematics
    • Physics
    • Natural Language Processing
    • Physics
    • Programming Languages
    • Data Modeling and Evaluation
    • Algorithms
    • Probability and statistics

Career prospects in Machine Learning and Artificial Intelligence

According to Indeed, here are the most in-demand jobs that require Machine Learning and Artificial Intelligence skills:

Machine Learning Engineer: Salary $142,859

These are skilled programmers who develop Artificial Intelligence systems that can learn from data sets. Machine Learning engineers require strong data management skills as well as the ability to perform complex modeling using dynamic data sets.

Top online Machine Learning Engineering courses:

  1. Introduction to Machine Learning Nanodegree by Udacity
  2. Masters in Machine Learning by Edureka
  3. Python Machine Learning Certification by Edureka
  4. Machine Learning by Stanford University
  5. Machine Learning by University of Washington
  6. Machine Learning Fundamentals by UC San Diego

Deep Learning Engineer: Salary $75,676

Deep Learning engineers are computer scientists who use deep learning algorithms to develop programing systems that take after the brain function. Deep Learning engineers must be experienced in developing neural networks.

Top online Deep Learning engineer courses:

  1. Applied Deep Learning Capstone Project
  2. Deep Learning Fundamentals with Keras
  3. Deep Learning by DeepLearning.ai
  4. Neural Networks and Deep Learning
  5. Deep Learning with Python and PyTorch
  6. AI Deep Learning with TensorFlow

Senior Data Scientist : Salary $134,346

These professionals use the organization’s data to enhance its capabilities using advanced statistical procedures. A data scientist is a computer scientist or specialized mathematician who is capable of collecting and cleaning data. They may use experimental frameworks for machine learning and product development to set up a strong foundation for advanced analytics. They are also responsible for developing the organization’s data-driven culture.

Top online data science courses:

  1. Introduction to Data Science by IBM
  2. Applied Data Science with Python by University of Michigan
  3. Master of Computer Science (Featuring Data Science Track) by University of Illinois 
  4. Data Science Fundamentals with Python and SQL by IBM
  5. Data Science: Capstone by Havard University
  6. Data Science Masters Program

Computer Vision Engineer: Salary $126,400

These professionals determine how computers can be programmed to achieve higher levels of understanding through digital image and video processing. Computer vision relies on massive data sets to train computer systems to read and interpret visual images.

Top online computer vision engineer courses:

  1. Computer Vision and Image Processing Fundamentals by IBM
  2. Computer Vision Basics by University of Buffalo
  3. Advanced Computer Vision with TensorFlow by DeepLearning.ai
  4. Computer Vision Nanodegree by Udacity
  5. Master of Computer Vision by HSE University
  6. Computer Vision in Microsoft Azure by Microsoft

Final thoughts

Machine Learning and Artificial Intelligence are closely correlated parts of computer science. The two technologies are increasingly gaining traction for creating intelligent systems. With Artificial Intelligence, you can ask machines questions and get feedback about inventory, fraud detection, customer retention, and more. And as more and more businesses and industries integrate Machine Learning and Artificial Intelligence into their operations, the demand for these technologies is definitely bound to rise.

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