Without a doubt, Artificial Intelligence (AI) and machine learning (ML) will be a top investment for businesses in 2019 and beyond. According to a 2018 survey, over 61% of companies indicated ML and AI are part of their most significant initiative for this year. (Source: MemSQL Survey).
What’s the reason for this increased investment? Companies understand how these revolutionary capabilities reduce the manual effort often required to perform relatively simple tasks. Implementing AI processing can result in upwards of several millions in cost savings for traditionally manual processes.
This is still an evolving trend, but the applications for AI is all around you. The world is full of highly sophisticated technologies to help automate and make things easier for you and me.
In addition, the career opportunities for machine learning engineers are endless as more companies adopt the technology. This is why 2019 is a perfect time to pursue training in this expanding field.
Before we get into our recommended certifications, lets explore real-world applications of this technology in our everyday lives.
What are common personal or home uses for Artificial Intelligence?
- Performing a Google search uses machine learning to look at millions of data points to return results most relevant to your query. Google Assistant is also being added to TVs, speakers, cars, phones, and other devices around the home. It provides tailored recommendations and simplifies interactions with the technologies.
- Asking a question or giving a command to Amazon Alexa uses AI to determine the appropriate response for Alexa. Shopping on Amazon results in personalized recommendations for products that have been determined based on your previous interactions with Amazon.
- A large number of TVs and smart home devices are adopting AI to give users more control and automation of everything around your home.
- Health technology and wearable devices (e.g., Apple Watch, Fitbit) use machine learning to provide insights and drive behavior. They use historical data to identify trends to alert you or provide recommendations to improve your health.
The processing power behind these and many other devices you can find in your home and office is beyond incredible.
These are complex systems being developing to augment and replace the manual tasks humans have historically done. All of this intelligence is built into your smart TV or even the phone you carry with you all day, every day. And it’s just in the early stages of adoption.
How do companies use AI & machine learning?
Machine learning technology has countless applications when it comes to the business world. Think about any manual task you see someone doing repeatedly around the office, job site, or factory floor. Each is an opportunity to apply machine learning to understand and automate those repetitive tasks.
- Customer service call centers have adopted sophisticated AI “bots” that can understand natural language. This allows the bots to interact with you and provide information you need faster with better accurately. This drastically cuts down the number of calls a customer service agent needs to take.
- Manufacturers are applying machine learning to the production floor. Systems are getting so smart they can predict anomalies in machine measurements in real-time. This helps to identify potential part failures that would result in operational downtime and loss of revenue. This is saving companies thousands or millions of dollars in some cases.
- Another application of the technology is through continuous monitoring and optimization of resources. Companies are using AI and machine learning to optimize production throughput based on efficiencies identified through intelligent analysis of staff quality, timeliness, and productivity. This ensures the right product is worked by the right person, at the right time. This results in reduced costs and higher quality for customers.
- Machine learning has also started to take over many repetitive back office processing. The technology can be applied to the processing of invoices, cutting paychecks, validating customer data, or executing marketing campaigns. This is just a short list, there are plenty of areas where AI can automate or assist in streamlining business processes. These are often tasks that have a set list of activities that are performed on a regular schedule.
This is a trend that is just starting to grow as more business realize the value it offers. This means you can get in on the technology trend early which has many options when it comes to job opportunities.
What is artificial intelligence and machine learning?
There are a few useful things to know to help you understand the difference between machine learning and AI.
Artificial Intelligence (AI) is about designing computer systems to mimic and enhance decision making typically made by humans to reach an outcome.
Machine Learning (ML) is about building computer systems to continuously evaluate and learn from data to make improvements to algorithms (processing logic). The goal is to increase the accuracy of an action or response over time based on historical data points and improvements.
The brief explanation is that machine learning is a systematic implementation or application of AI.
What experience is required to pursue a career as a machine learning engineer?
It’s recommended to have an education in data sciences, however, you can by with an engineering or computer science background. Machine learning leverages analytical models to evaluate permutations in data to identify the best responses or actions and continuously refine algorithms.
Many of the courses below provide an introduction to those concepts and walk through examples of how to define and apply the models. While the courses are challenging, they will enhance your passion and curiosity for AI.
Where can you get machine learning training?
Below are our top training and certificates to establish your expertise with machine learning technology. They are excellent courses regardless of your experience level. Several also provide a certificate after completion.
1. Machine Learning Certification Course – Simplilearn
This is an excellent online course which provides over 36 hours of instructor led training. The course uses four integrated labs and over 25 exercises to build hands-on experience with building and applying AI. Most online certification training programs only allow access for 90-180 days, but Simplilearn provides life-time access. You can review the self-paced training content at any time. Take advantage of the discount offer below to save on your learning now.
2. Machine Learning – Stanford University (Coursera)
Taught by Andrew Ng who co-founded Google Brain and helped to vastly expand Baidu’s artificial intelligence team. This course introduces several concepts and practical applications of supervised and unsupervised machine learning. This is a course you will want to take multiple times to fully grasp the concepts. However, it has the highest rating for a machine learning course on Coursera at 4.9/5.0 based on 90K+ ratings.
3. Machine Learning Specialization – University of Washington (Coursera)
Taught by UW’s Amazon Professors Carlos Guestrin and Emily Fox, this is a 4 part course to earn a specialization certification in machine learning. The initial course introduces various case studies that will to help you understand the foundational concepts. The remaining three courses dive deep into defining Regression, Classification, Clustering, & Retrieval models to apply machine learning in multiple scenarios. The content does get technical, but does a great job of engaging you in real-world applications. All four courses rate 4.6/5.0 or above.
4. Machine Learning: From Data to Decisions – MIT
This eight (8) module course from MIT starts by building a foundation of knowledge across various ML concepts. The subsequent modules then demonstrate applications of prediction models to make decisions and inferences. The value of this course is outstanding. You earn a certification from a leading university on the topic of artificial intelligence and machine learning.
5. Nanodegree: Become a Machine Learning Engineer – Udacity
This incredible course is highly rated and well known across the industry. Udacity’s nanodegree program takes you from foundational machine learning topics to applying advanced concepts through real examples. You’ll gain great experience and a machine learning nanodegree with this course. This will make you the top ML expert at your current or future employer.
If you just want a basic introduction to the topic, we’d recommend starting with Udacity’s free Intro to Machine Learning course.
Conclusion
You can’t go wrong with any of the above learning options. Each course will help build foundation understanding, whether you are looking for a career change or simply want to learn more about the topic.
Most of the courses are taught by instructors from well known data science and artificial intelligence programs at highly respected learning institutions.
AI and machine learning are skills that are in high demand by all employers. This is a trend that’s only going to increase. Companies are just starting to figure out how to harness this technology to automate business processes.
Right now is the perfect time to get certified and become an expert with this technology.
Have fun learning and please share any comments below.
