The journey to a successful career in leading fields begins by choosing from the top AI and ML courses and training resources. The ones mentioned here are among the best ones.
Artificial intelligence and machine learning are two highly adopted technologies simplifying everyday tasks for everyone. These two are rapidly being adopted for both professional and personal utilization throughout the globe. This boils down to the conclusion that a great future awaits those who decide to gain skills in these technologies.
To get started in the tech world, one must get their hands on the right training resources. This blog compiles the top 5 AI and ML courses and training resources offered online to get started.
Top 5 AI and ML Courses
Those who wish to learn AI and machine learning should get started by sifting through the best AI and ML courses. Only the best online AI and machine learning course can cement the chances of success. Here is a list with the top five courses and training resources to rely on to learn ML and AI.
Machine Learning & Artificial Intelligence Online Training by igmGuru
This artificial intelligence and machine learning online course by igmGuru is a leading choice amongst aspirants. It's apt for those who are just beginning out as well as for those having prior working experience. It's taught by seasoned industry professionals with 10+ years. It's a well-crafted, paid course with watch 1st class free to get a better understanding of the teaching style. The course material is very well-rounded and smoothly articulated. Two options to pick from are live, instructor-led classes and a self-paced learning program. It's certainly the best machine learning course out there. Curriculum covers -
Introduction to AI & ML
Techniques of ML
Data preprocessing
Math refresher
Regression
Classification
Unsupervised learning: clustering
Introduction to deep learning, etc.
AI Foundations for Everyone by IBM
AI Foundations for Everyone is a beginner-level course for anyone who's looking to learn at their own pace. As the name suggests, it's focused primarily on the foundations of AI. With four core modules, this program is everyone looking to understand artificial intelligence, and not just engineers. It's taught by Andrew Ng, who is a renowned Stanford professor. The focus of this paid course is to give a chance to non-tech people to gain a good understanding about the working of AI. It uncovers various associated topics like -
Associated terms like ML, DL, neural networks & data science.
Navigating social & ethical discussions around AI.
Stopping AI opportunities.
Building AI strategies, etc.
Machine Learning on EdX by Columbia University
This Machine Learning course by Columbia University is an advanced level program. To enroll in this particular course, one needs good, in-depth math skills and knowledge. It's a free course but anyone who needs a certification must pay $300. Due to its high level prerequisites, this course is often picked by only those with in-depth knowledge. It's a continuously growing field and courses like this one enable experts to upskill themselves. Probabilistic approach to ML is covered here, which is an advanced-level aspect. Key concepts covered are -
This ML crash course is by Google AI Education, which is a totally free platform containing videos, interactive content and articles. Every section of the program uncovers a certain specific aspect of ML that makes it easier to learn about this technology. It's free of cost and can be availed by anyone interested in learning ML basics. All articles and videos lectures are delivered in a crisp manner, and are easy to understand. Those interested in self learning will benefit tremendously. The curriculum includes-
ML engineering
Linear & logistic regression
TensorFlow
Model performance metrics
Classification
Neural networks
Feature engineering & cleaning data
Embeddings
Training & loss
Training sets, validation & splitting
Feature crosses
Overfitting, etc.
AI for Business Specialization by University of Pennsylvania
Get started on the journey to learn the fundamental concepts of artificial intelligence and ML. Top concepts covered here are ML, AI and big data to support the business through their best practices. It's great for beginners who wish to learn at their own pace. In fact, this is not just restricted to AI but spreads to effective marketing strategies through data analytics. Learn about personalization, AI ethics and risks, people management and designing governance frameworks here. It covers topics like-
AI applications in finance & marketing.
AI governance & strategy.
Non-data scientist AI fundamentals.
AI implementation in people management.
Handling & interpretation of big data.
Extending customer lifecycles.
Wrap-Up
There is no end to the number of AI and ML courses out there. In fact, the internet is full of those. The key here is to pick out the best one in the lot that aligns well with career goals and existing knowledge. The list here covers the best ones that are trusted by learners on a global level. Stepping in the world of ML and AI is not an easy task. Unless otherwise mentioned, these courses generally require good knowledge of mathematics and programming languages. This narrows down the audience apt for such programs but also ensures it reaches the right people.
FAQs For AI And ML Courses
Q. What are the prerequisites for Online AI and Machine Learning Course?
Some key prerequisites for online AI and machine learning course are-
Strong grasp on mathematics - statistics, calculus, modeling, algebra, probability, etc.
Good programming skills - Python, Java, R, C++ , etc.
Strong analytical skills.
Q. Which are the top AI courses for beginners?
Top AI courses for beginners are provided by igmGuru, Udemy, IBM and Google.
Q. After completing AI and ML Courses, what is the salary of an AI engineer?
The salary of an AI engineer in the US is around $153k per year on an average.
Q. Which company is number 1 in artificial intelligence?
The number one company in artificial intelligence as of today is Microsoft. It is closely followed by NVIDIA, Google, and Meta.
