With more than 2.5 quintillion bytes of data getting generated each day, businesses are continuously looking to derive valuable business insights from such data. Marketwatch forecasts that the total market value of Artificial Intelligence will grow to $191 billion by 2024 at CAGR of 37%. Data Science and AI are poised to unleash the next wave of digital disruption, and organizations can prepare for it now by taking up our courses in this field that cover a comprehensive range of topics.
What is Machine Learning / Artificial Intelligence?
Machine learning involves computers discovering how they can perform tasks without being explicitly programmed to do so. It involves computers learning from data provided so that they carry out certain tasks. For simple tasks assigned to computers, it is possible to program algorithms telling the machine how to execute all steps required to solve the problem at hand; on the computer’s part, no learning is needed. For more advanced tasks, it can be challenging for a human to manually create the needed algorithms. In practice, it can turn out to be more effective to help the machine develop its own algorithm, rather than having human programmers specify every needed step.
Machine learning approaches
Machine learning approaches are traditionally divided into three broad categories, depending on the nature of the “signal” or “feedback” available to the learning system:
- Supervised learning: The computer is presented with example inputs and their desired outputs, given by a “teacher”, and the goal is to learn a general rule that mapsinputs to outputs.
- Unsupervised learning: No labels are given to the learning algorithm, leaving it on its own to find structure in its input. Unsupervised learning can be a goal in itself (discovering hidden patterns in data) or a means towards an end (feature learning).
- Reinforcement learning: A computer program interacts with a dynamic environment in which it must perform a certain goal (such as driving a vehicleor playing a game against an opponent). As it navigates its problem space, the program is provided feedback that’s analogous to rewards, which it tries to maximize.
How is the role of AI increasing in the post-COVID era
As an aftermath of the global pandemic, industries all over are witnessing an accelerated adoption of AI-led technologies in order to ensure business continuity during the changed circumstances. Because of the increased number of functions being automated, creating a need for more skilled tech talent.
The Fourth Industrial Revolution has boosted not just the creation of jobs in the space but also the interest in AI-related jobs, as job searches have seen a consecutive increase in the last five years. Job openings for AI-related jobs have seen a 28% increase from August 2019 to August 2020, while job searches have seen a 91% spike.
Novelstrat Machine Learning Certification Training using Python helps you gain expertise in various machine learning/AI algorithms such as regression, clustering, decision trees, random forest, Naïve Bayes and Q-Learning. This Machine Learning using Python Training exposes you to concepts of Statistics, Time Series and different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms.
Please download the syllabus using the below link-