The next digital frontier in the IT world is?
The one that is your opponent in PUBG(or other interactive games), that allows you to ask Google to make calls for you, that reminds you to make your insurance paid, suggests what to purchase from your favorite eCommerce site, and suggests movies over Netflix.
We are surrounded by Artificial Intelligence and Machine Learning applications so extensively that we don’t even realize their presence. When Facebook recommends friends or groups to you, it is AI working behind the scenes. When Google listens to you and acts as per your command, it’s ML and AI working.
Grandview Research states that there is 57.2% annual growth expected in the global AI and ML market. According to Fortune Business Insights, the global market size of Artificial Intelligence is expected to reach USD 202.57 billion by 2026.
Another report by Forbes states that Artificial Intelligence may create around 58 million new jobs worldwide by 2022.
AI ML certification is the best way to make a career in a technology that is ever-evolving and is full of innovations at each and every step. With the certification, you can get a well-paying job in any corner of the world.
Let us now move ahead to what AI and ML technologies are and what skills are required to get into a profession in the same.
What is Artificial Intelligence?
According to an AI researcher at Google and creator of ML software library Keras, Francois Chollet, ‘Intelligence is the efficiency with which you acquire new skills at tasks you didn’t previously prepare for’.
So, when this intelligence is shown by a machine or computer, it is Artificial Intelligence. Artificial Intelligence is the simulation of human intelligence in machines. The machines are programmed in such a way that they are capable of thinking like humans and imitate their actions.
What is Machine Learning?
The cornerstone of AI is Machine Learning. It is a subset of Artificial Intelligence that enables software applications to become more efficient at predicting without being explicitly programmed for that.
The most common applications of Machine Learning that we can come across in our daily lives are recommendation engines, fraud detection, malware threat detection, spam filtering, predictive maintenance, and business process automation or BPA.
Skills Required for AI and Machine Learning
1. Programming Languages
Python is the lingua franca of Machine Learning.
2. Neural Network Architectures
Machine Learning is generally used for complex tasks that humans cannot code. The most efficient way of countering problems like speech recognition, image classification, translation, image classification is neural networks. So, it is crucial to have a sound understanding of neural network architectures.
3. Linear Algebra, Calculus, Statistics
It can be helpful if you have a good understanding of vectors, matrices, and matrix multiplication. A knowledge of derivations and integration and its implementation can also be great.
Also, you need to have a sound understanding of statistical concepts like standard deviations, mean, and Gaussian Distributions and probability theory, including Hidden Markov Models, Gaussian Mixture Models, Naive Bayes, and other concepts are necessary.
4. Signal Processing Techniques
Proficiency in signal processing techniques and their implementation to solve different problems is crucial when you need to perform feature extraction, which is an important aspect of Machine Learning.
Signal Processing Techniques also include Time-frequency Analysis and also advanced signal processing algorithms that may include Shearlets, Wavelets, Curvelets, and Bandlets.
5. Applied Math
When you have a solid foundation of math and algorithms, it becomes easy for you to understand concepts such as Convex Optimization, Gradient Descent, Quadratic Programming, Lagrange, Summations, Integration, and Partial Differentiation.
1. Communication Skills
The most important soft skill for any profession is excellent communication skills. You are required to work in a team and also interact with business partners and stakeholders. To make this task effective, you must possess great communication skills, both verbal and written.
2. Rapid Prototyping
It is important to keep working on the plan with the minimum time consumed. Rapid prototyping helps you in selecting the right model and forming multiple techniques to speed up developing a scale model.
3. Domain Knowledge
You should possess a profound knowledge of how your domain works, regardless of the industry you are working in. The domain knowledge enables you to finish the project without any flaws.
Sound domain knowledge also allows you to interpret potential difficulties and the solutions to them.
1. Language, Audio, and Video Processing
With the sound knowledge of NLP, you can get to work with prominent areas of work like Computer Science and Linguistics, including audio, video, and text. You will have to be well-versed with libraries such as NLTK, Gensim, and techniques like Sentiment Analysis, word2vec, Summarization.
2. sPhysics, Reinforcement Learning, and Computer Vision
Sound knowledge of physics, like application of machine learning; and reinforcement learning include robotics, self-driving cars, or other AI applications; Computer vision to control complex systems that depend on CV and Machine Learning algorithms.
The Wrap Up
Now that you have read about all the skills required to enter into the world of Artificial Intelligence and Machine Learning, what can be done to acquire these skills?
The smartest way to acquire these skills is to take up an online training course such that you get to schedule your learning hours, select from the different learning modes and no worries about arranging the study material. Industry experts conduct Ask Me Anything sessions to help you out with all your queries. With round-the-clock learners’ assistance and career guidance, what else would you wish to have?