Free Online AI and ML Courses

The key differences between AI and ML are:

We provide free resources, such as blogs, tutorials, and videos, as well as a community where you can learn a lot about AI and ML from subject matter experts. We also provide free courses related to AI and ML that you can start learning to build up your basics.

Deep learning is a subset of ML. Deep learning is concerned with algorithms that are inspired by the structure and function of the brain. These systems are known as artificial neural networks.

The core of deep learning is the capability of training large neural networks due to the present existence of fast enough computers and sufficient data. As larger neural networks are constructed and trained with more and more data, their performance improves significantly. Deep learning is generally different from other ML techniques that reach a plateau in their performance.

There are no prerequisites mandated to start learning AI and ML. As long as you have a good internet connection, you can start taking these free courses.

You can start your journey by learning the fundamentals of AI such as NLP using Python, neural networks and deep learning, logistic regression, linear regression, ML with TensorFlow, time series analysis, etc. Learning the fundamentals will help you get started in your journey to become an AI Engineer in no time.

Today, AI has either conquered or is knocking on the door of almost every industry. In the near future, nearly 80% of emerging technologies will be based on AI.

ML, especially deep learning, is used by AI-powered recommender systems, chatbots, and search engines for online movie recommendations and several other applications.
Therefore, AI and ML can be a rewarding career option. Gaining all the right competencies will help you get a high-paying job in top MNCs around the world.

Many companies are seeking skilled candidates in ML for their AI-powered projects. With the rapid growth of AI and ML in every area, the future for professionals in this domain looks promising.

According to Glassdorr, AI engineers in India earn an average of about ₹949,364 p.a. and about US$119,297 p.a. in the USA.

According to Glassdoor, ML engineers in India earn an average of about ₹898,509 p.a. and US$131,001 p.a. in the USA.

Some of the job responsibilities of an AI engineer are:

• Evaluating and comparing algorithm performances based on large datasets
• Data mining from multiple sources and deriving insights
• Designing and implementing ML algorithms
• Accelerating existing algorithms and models
• Establishing scalable model validation, model implementation, and large-scale data analysis
• Conducting research to determine technical solutions at scale for real-world challenges in various scenarios

Some of the job responsibilities of an ML engineer are:

• Designing ML systems
• Researching and implementing algorithms and tools
• Performing statistical analysis
• Verifying data quality
• Executing ML tests
• Choosing appropriate datasets
• Extending ML libraries
• Developing ML apps as per client requirements
• Transforming and converting data science prototypes
• Using results to improve models
• Training and retraining systems when required
• Choosing the appropriate data representation methods
• Recognizing differences in data distribution that impact
• model performance