Artificial intelligence (AI), machine learning (ML), deep learning (DL), and data science (DS) are some of the modern technologies that are dominating the world.
Unlocking smartphones with our faces, getting virtual assistance on online websites with chatbots, having unwanted emails filtered to the spam folder without opening them, etc., are examples of how AI and ML are dominating and transforming laypeople’s lives.
Furthermore, with an increasing number of companies constantly introducing innovations, the scope for developing new technologies like AI, ML, and DS is limitless.
Organisations are harnessing the potential of AI and machine learning to streamline processes internally and analyse information to build a knowledge pool to ensure their overall growth.
As more and more companies increasingly rely on AI and Machine learning for their growth and functioning, the need for new-age skilled AI and ML professionals is also growing to handle projects and fill the talent gaps in the industry.
So, if you want to make a fulfilling career in artificial intelligence, read through this step-by-step guide.
How to Start a Career in Artificial Intelligence?
You need to follow the steps listed below:
Step 1: Learn the Basics
Below we have mentioned skills that an AI professional must possess. While it could be hard to acquire all of them, having a focused approach could lead to good outcomes.
To develop a career in AI, you need to be well-versed in different programming languages like Python, Java, R, C++, etc. M.Tech in AI’s comprehensive curriculum can help you understand programming basics. It will also make you aware of commonly used algorithms and how AI or ML models are created
Did you know: A programming language is a computer language used to develop software programs, scripts, or feed instructions into different machines?
Python, Java, and C++ are a few of the most used programming languages in AI and ML systems. It provides them with tools to perform activities similar to a human brain.
Mathematics and Statistics
An AI professional must have in-depth knowledge and interest in mathematics, statistics, and probability. Because it helps them develop programmes that can surpass the intelligence of the human brain, perform complex tasks, prioritise critical work, and function without human intervention.
Moreover, in this day and age, having a solid hold over statistics helps data science or AI professionals make sense of the enormous data sets, identify patterns, and build better machine learning and artificial intelligence models.
Did you know: You need to have statistical, mathematics, and programming skills to excel in AI. While statistical skills are required to understand complex algorithms and identify patterns, programming and mathematical skills are required to ensure the smooth functioning of AI and ML models.
Machine Learning Algorithms
You must understand different types of algorithms and how they work to develop and design AI and ML models because they form the foundation of AI-powered systems. ML algorithms are unwritten rules and regulations or instructions that the machine has to follow while performing tasks.
It also helps identify data patterns and makes predictions or recommendations about trends.
How Can You Learn Machine Learning Algorithms?
You can learn the basics of machine learning algorithms by taking advanced courses.
Undertaking certificate courses in machine learning from Emeritus India can help you build a strong foundation in ML algorithms. These learning programmes equip you with skills to make a real difference across industries.
Common AI Concepts
Natural Language Processing (NLP) and Computer Vision (CV) are an artificial intelligence system’s two most critical pillars –
- NLP allows modern machines to understand human language. It provides modern systems with tools and tips to interact and learn from their environment.
- CV allows machines to see, understand, comprehend, and interpret the environment around them. It is generally used in object recognition, image search, etc.
NLP and CV together teach AI systems to interact, adapt, and learn from their environment. They also help AI and ML machines achieve human-level accuracy and performance. Therefore, to succeed in the field, you must be well-versed in them.
Step 2: Gain Experience Working with Data
Data is an essential element of AI or ML machines. It helps machines update themselves and learn from their mistakes.
AI or ML machines act as a part of the human brain that analyses a situation and makes a decision based on data accumulated and collected from the past.
You can take different data science courses to understand the basics of data and get used to working on large data sets.
Step 3: Take Up Advanced Training Programmes
With the rapid development of AI and ML and an increased number of companies introducing AI into their businesses, the demand for professionals with advanced skills is increasing. To compete and stand out from the crowd, it is essential to undertake certification or executive courses that help you acquire in-demand skills and add value to your resume.
Emeritus India offers an array of certification courses in data science, artificial intelligence, data analytics, and similar fields. We have partnered with renowned Indian universities to provide these learning programmes with a knowledge-rich curriculum. Enrolling in any of them will help you skyrocket your career.
Why Start a Career in Artificial Intelligence?
From a career perspective, AI and ML professionals are expected to be the fastest-growing professionals globally. A report revealed that job opportunities in AI have almost doubled between June 2015 and June 2018. The report further revealed that the jobs requiring AI skills have increased by almost 40%.
Here are some reasons you must consider pursuing a career in artificial intelligence.
- AI is a lucrative field for mathematics, statistics, and probability students. An entry-level AI professional earns INR 6,00,000 per annum. Meanwhile, a senior-level AI professional can earn INR 50,00,000 annually in India.
- Artificial intelligence is widely used across different industries like healthcare, marketing, logistics and information technology, leading to an exponential increase in demand for AI professionals.