In this AI-driven generation, the importance and relevance of artificial intelligence can’t be neglected. With AI tools such as Midjourney and ChatGPT becoming an integrated part of the tech industry, a career in AI is becoming a lucrative option.
If you are still thinking of how to start a career in AI or how to become an AI engineer, then this is the one-stop guide for you. We will be covering every aspect of AI from scratch and covering the right skills to launch a career in AI.
What does AI or artificial intelligence mean?
Artificial intelligence, popularly known as AI, is a distinct branch of computer science that deals with creating tools to perform certain tasks that would usually be dependent on human intelligence. From comprehending natural language to analysing user behaviours and making data-driven decisions, these tasks make all of these easier. AI is a broad subject with a lot of subfields. We’ll look at these subfields now; this knowledge will guide how to start a career in AI.
- Artificial Super Intelligence (ASI): This is the ultimate stage of AI. It refers to the situation where AI will emerge greater than human intelligence in almost every economic sector. This concept will take time to get implemented.
- Artificial Narrow Intelligence (ANI): This is the most used branch of AI today. ANI is primarily focused on performing a single task at a time, like voice recognition or personalised recommendations on streaming platforms based on user behaviour.
- Artificial General Intelligence (AGI): AGI has the prowess to study, analyse, and implement expertise across many human-oriented tasks and fields. A tool like ChatGPT is one of the leading examples of AGI.
Professionals belonging to the IT sector thinking of starting a career in artificial intelligence, have a great number of options. For those confused about how to become an AI engineer or how to start a career in artificial intelligence, the following career paths along with their dedicated skill sets will give more clarity.
AI Engineer
The role of AI engineers is to create, build, and implement AI systems. Those who are eager to know how to become an AI engineer, have a thorough knowledge of programming languages like R, Python, and Java, and also have expertise in machine learning frameworks like PyTorch. AI engineers have to focus on creating algorithms and come up with AI solutions to meet specific business needs.
AI Ethicist
As AI continues to grow rapidly, there is a huge demand for professionals who can adhere to ethical conduct and ensure the proper development and deployment of AI. AI Ethicists define ethical guidelines on which AI should function and study the impact of AI on society. This is a great career option for those who are thinking about how to start a career in AI.
Machine Learning Engineer
These engineers primarily create and implement algorithms and systems based on machine learning. Their roles include data analysis, model training and evaluation, and feature engineering. Knowing R or Python is essential for this job.
AI Solutions Architect
The primary job of AI solutions architects is to create and exercise AI-driven solutions that cater to certain business needs. This job is more collaborative-oriented; they need to work with cross-functional teams to determine business needs, recognise AI opportunities and create scalable AI architects. Having great problem-solving skills along with a background in system design fits the best for this job profile.
Data Scientist
For those who are looking for answers on how to start a career in AI, the most popular careerpath is that of a data scientist. This job role requires proficiency in analysing statistics, and implementing machine learning techniques. They should also know data mining algorithms to determine patterns from a pool of data sets. Having experience in data manipulation and impressive analytical skills along with machine learning are the key skill sets required for this role.
AI Product Manager
AI product managers manage the creation and implementation of AI-driven services and solutions. To provide superior AI solutions, they work with engineering groups to establish the product goal, evaluate attributes, and define features. For this position, one must have outstanding communication abilities, business skills, and a technical understanding of AI.
AI Research Scientist
Researchers working to further the understanding of artificial intelligence are known as AI research scientists. Their tasks include creating fresh computations, refining current models, and investigating creative uses for artificial intelligence. For this position, one must have a solid foundation in mathematical theory, computer science, and machine learning, in addition to academic experience and the ability to think critically.
Important AI Tools and Packages
Acquiring skills in the right tools and packages is vital to launching a career in artificial intelligence. Python and R are the two most in-demand languages in the market. You specifically don’t need to learn both to succeed in AI. In this portion, we wil explore the major Python tools and packages that will further clear your doubts about how to start a career in AI.
Major Python AI tools and packages
Python is a programming language that interprets code at an advanced level and is renowned for its clarity and versatility. Because of its straightforward syntax and the abundance of data science and AI resources available, it is frequently employed in artificial intelligence.
pandasÂ
A Python package called pandas offers a variety of tools for studying data. pandas is a tool used by data analysts for activities such as statistical evaluation, data alteration, and data cleansing. It is an important tool for preparing databases since it performs effectively with clogged, unfinished, and unlabeled information.
LangChain
Currently, LangChain is among the most widely used artificial intelligence platforms. It enables developers to incorporate AI derived from big language models into programs and information pipelines.Â
Scikit-Learn
A straightforward and effective tool for data exploration and machine learning, Scikit-Learn is based on matplotlib, SciPy, and NumPy. It is open-source, which means anybody may use it for free. Numerous techniques for grouping, modelling, categorisation, and dimensionality reduction are included.
Keras
Python-based Keras is a simple-to-operate artificial intelligence library. It provides a simple method for neural network modelling and is designed to reduce the time between concepts and functional models. In addition, Keras is adaptable, which greatly expands its potential for creating fresh models.
Hugging Face
Once users gain experience, they can easily use GPUs and TPUs by exploring models that have been trained with popular Python packages like Hugging Face's transformers and accelerate.
NumPy
NumPy, aka Numerical Python, is an extension of Python that offers extensive functionality for handling big, complex arrays and matrices. It also provides a vast variety of sophisticated mathematical algorithms that can be employed for these arrays. Any computation used in science, notably AI, requires a library like this.
PyTorch
A free neural network library called PyTorch is built based on the Torch library. Systems like artificial neural networks and natural language processing employ it. Its quickness and versatility make it ideal for learning-based studies, which is its greatest asset.
How to Start a Career in AI: Required Skills
It is quite tempting and intriguing to know about the varied possibilities of AI. Here is a set of skills and tips that will give all the answers on how to start a career in AI.
Learn Programming Skills
Competence in programming languages is essential for anyone hoping to work in artificial intelligence. Python's ease of use, adaptability, and abundance of AI and deep learning tools make it the preferred language for developing AI applications. Furthermore, based on the user's particular area of expertise within AI, proficiency with programs like C++, Java, or R may be advantageous.
Specialisation in One Filed
Artificial Intelligence is a broad, interdisciplinary field that includes imaging, automation, machine learning, and other areas. Decide which AI fields most fascinate and excite the most, then concentrate on learning and developing specialised abilities and expertise in those fields. In addition to helping users stand out from the competitors, specialisation leads to more prospects in specialised jobs.
Learn Soft Skills
Good interactions, problem-solving, and collaborative abilities are also very important in AI positions, alongside technical expertise. Companies look for applicants who can work in interdisciplinary teams, express complicated ideas well, and adjust to changing circumstances.Â
Know the Basics
Establishing a solid knowledge base is crucial before delving into the complexity of artificial intelligence. Learn about important ideas, including visual computing, natural language processing (NLP), neural nets, artificial intelligence, and deep learning. Enrolling in a generative AI course can also help in mastering the basics of AI.
Gain Experience through Internships
Before landing the first AI gig, it might be necessary to start with entry-level jobs or internships to obtain real-world skills and access to the industry. Look for internships or entry-level positions in startups, academic institutes, and businesses that are focused on artificial intelligence.Â
The Best AI Certifications
We have covered extensively how to start a career in AI, in this blog. Now it is time to talk about the top 3 AI certifications that will guarantee a breakthrough in the AI industry. The certifications are as follows:
AWS Certified Machine Learning
This certification, offered by Amazon Web Services (AWS), verifies the user's ability to design, implement, launch, and sustain ML services on AWS. It covers a wide range of machine learning principles, including feature engineering, data science, model development, and optimisation.
Microsoft Certified Azure AI Engineer Associate
This Microsoft certification confirms that users can design and execute AI solutions using Microsoft Azure. It includes a variety of AI services offered by Azure, such as cognitive services, ML and NLP.
AI Fundamentals (AI-901)
The AI-900 Microsoft Azure AI Fundamentals certification offers a thorough overview of AI in the Azure environment. This course covers key AI topics and Azure AI services, giving students a solid understanding of neural networks, image processing, natural language processing, and data analytics.
Summing Up
Artificial intelligence is not far behind in changing the entire landscape of the tech industry. And in this rapidly changing tech world, acquiring knowledge of AI and its various tools will be a great boost for professionals, especially those with mathematics and computer science backgrounds. We hope that this blog has adequaltely answered the pertinent question of how to launch a career in AI.
Enroll in Imarticus’ Advanced Certificate Programme in Generative AI in Association with E&ICT Academy, IIT Guwahati to launch a career in artificial intelligence.
Frequently Asked Questions
Who will benefit from learning AI?
AI can benefit anyone. AI is completely revolutionising decision-making and problem-solving. Professionals apart from software engineers and data analysts can benefit from AI as well.
What are the skills required to learn AI?
Thorough knowledge of linear algebra, probability, Python, data science, data manipulation, and machine learning can help one learn AI faster.
Why is learning AI beneficial now?
AI is a fast-growing sector with exceptionally high pay and is intellectually challenging. So, to sum up, it is the call of the hour.
Is it possible to get a job in AI without a degree?
Yes, a degree is not a mandate for a job in AI. Learning more about AI and its latest trends and sharing works on platforms like LinkedIn can attract high-paying jobs.
