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Jobs you can get after completing Machine Learning and AI courses

New technologies are rapidly getting adopted throughout the globee. And when it comes to ML and AI we see that the adoption rate is extremely high. AI has already made its impact on different products such as digital disease diagnostics, self-driven vehicles, and robot assistance, influencing the way we live and function. AI will be the revolution of this century. 

In recent years, the demand for qualified engineers has more than doubled. Therefore, the people who want to work in research and development have been getting endless opportunities and different job roles. There are immense future opportunities for those who are upskilling themselves through AI and machine learning courses online.

A study conducted by Indeed suggests that the jobs of data scientists, machine learning developers, and software technologists are the most demanding opportunities in the machine learning and artificial intelligence sector. 

Fundamental Differences Between Data Science, Artificial Intelligence, and Machine Learning

The terms machine learning, artificial intelligence, and data science may be interrelated but they are also a unique domain in themselves.

Necessary Skills Required for Data Science Jobs

As the digital age unfolds, new career opportunities for data science are also rising. The area is proving to be an enticing choice for both undergrad students and professionals in their mid-level career paths. Additionally, data science as an insight-generation tool is being allocated separate departments and spaces at the enterprise level across media, heavy engineering, and other industries.

Core areas of data science jobs are being created in the processes of improvement of customer relations, product development, data mining for comprehensive reports on potential business opportunities, etc. Organizations world over are focused on data science for creating the need, growth, and sustainability of their corporations. This has led to the identification of a list of primary skills required for data science jobs, broadly classified into technical and non-technical skills.

Technical Skills Required for Data Science Jobs

The major technical skills required to become a data scientist are deep learning, statistical analysis and computing, data visualization, machine learning, data wrangling, programming, working with big data, and stats. Typical postgrad courses that include these skills are a master’s or Ph.D. degree in computer science, mathematics, engineering, and statistics. 

Non-technical Skills Required for Data Science Jobs

These are majorly dealing with soft skills like creative communication, strong business acumen, data intuition, and data visualization. 

Someone interested in pursuing data science as a career need not worry about not having a background in computer science, engineering, mathematics, or statistics as they can enrol in online certificate courses and online professional courses to get started with a career in data science. 

Necessary Skills Required for Machine Learning Jobs

To pursue a career in machine learning, professionals need to be well prepared to handle a challenging and exciting arena in terms of both technical and non-technical expertise. 

As an aspiring professional in this field, you need to remember that machine learning is ultimately feeding code into machines to get them to perform specific tasks. Hence, a machine learning expert must be passionate and well trained in programming and related concepts with constant upgradation as per the pace of research in the computing industry. 

The technical skills in demand for machine learning include the knowledge of physics, neural network architecture, data modeling, data evaluation, applied mathematics, advanced signal processing techniques, reinforcement learning, natural language processing, and audio and video processing.

A 2020 research, conducted by Gartner, also stated that 2.3 million jobs will be available globally in machine learning in the years following the aftermath of the COVID-19 pandemic. Mainly, software giants like Apple, Microsoft, Univa, Amazon, and Google are currently investing millions of dollars into machine learning development. 

The benefit of working in this domain is that they welcome both senior professionals and newcomers in the world of computing. Keeping this in mind, individuals having a non-technical background with an interest in machine learning can also enrol in a machine learning course online that equips them with skills like machine learning algorithms, system design, computer science fundamentals, and distributed computing. –

Necessary Skills Required for Artificial Intelligence Jobs

According to SEMrush, 75% of executives fear they will go out of business in the upcoming five years if they do not develop AI for marketing communications and other business processes. This explains the need for AI professionals in every department of a modern workplace right from media management, marketing, and production to product design. 

With great potential to transform global economies and societies, AI is considered the future of networking and computing. This makes it the most sought-after career option in technology, with increasing demands for full-time jobs in sectors like cybersecurity, IoT, healthcare, software, and automobiles.

Global corporations working in these sectors are using AI to construct cutting-edge services that can improve living standards, business processes, and the exchange of information by reducing complexities in communication. 

Thus, the most popular technical skills required for AI careers are knowing programming languages like python, C++, R, and Java. Also, one must have a strong grounding in domain knowledge; ability to work in frameworks and libraries such as SciPy, TensorFlow, and NumPy; familiarity with applied mathematics; in-depth understanding of predictive analysis through deep learning; and a knack for concepts like shell scripting, cluster analysis, distributed computing, and neural network architecture. 

Job Opportunities for AI and ML Candidates

Data Analyst

A data analyst majorly works with unstructured and unorganized datasets combining numbers, figures, and data for deriving logical conclusions. Their main task is to translate complex data into valuable information.

Machine Learning Engineer 

An ML engineer should hold expertise in C++, Java, Scala, Python, and JavaScript so they can create algorithms and decode patterns based on big data. They are also tasked with anomaly detection, classification of unstructured data, implementing applications, and predictive analysis.

Data Scientist 

Data scientists are experts in analytical and logical reasoning such that they can decipher heavy codes to build insights for the industry using their strong programming, statistical and mathematical skills.

Job roles in artificial intelligence:

Artificial Intelligence Engineer 

An AI engineer should command efficiency in handling industrial AI infrastructure other than developing AI algorithms for products and services.

Business Intelligence Developer 

This is a promising designation for the future where the role of business intelligence developers extends to assisting in optimizing business processes and smoothening complicated cloud-based computing for e-commerce giants.

Robotic Scientists 

Designing operating systems and testing mechanical devices grounding on the cost-functioning of corporations are the main responsibilities of robot scientists. Considering current trends, this profile will be in huge demand in the near future.

In a world where Alexa and Siri are becoming companions sharing our heartbreaks, successes, and failures, the significance of digital technology needs no introduction. CEO of Lattice, Shashi Upadhyay, famously calls machine learning and artificial intelligence professionals “unicorns” due to their complete package of uncommon skill sets in one individual. 

This holds true for the evolving data science jobs and industries involved. AI and ML professionals are uniquely equipped, technologically adept, and potentially of enormous value to the corporations they are hired by. 

While these technologies become handy and an inseparable part of our everyday lives, you cannot forget the dint of hard work and science that goes behind creating them. Stressing further, these skills of machine learning, data science, artificial intelligence, and advanced computing are becoming the norm of the day in the ongoing digitized world post the pandemic era. 

However, lack of awareness and fear of the unknown is restricting many individuals to pursue full-time careers in these fields, leading institutes like Hero Vired to emerge and bridge the gap between employees of today and those of the future. Hero Vired boasts of a wide range of comprehensive courses and skills training that is easily accessible sitting in any part of the globe.

Learn with Hero Vired

If you are passionate about data science and have no relevant educational background in mathematics or coding, then enroll immediately into the Hero Vired PG Certificate Program in Business Analytics and Data Science to fulfill your big data dream. 

This course is designed mainly for freshers and mid-level professionals providing them an in-depth knowledge of Python along with fundamental training in mathematical algorithms combined with statistical models. 

The learners will be taken through an intense 3-week session enabling them to analyze, visualize and design the intricacies of data analysis. The eligibility criteria for this program include a bachelor’s degree with a basic idea of programming languages like Python. Those not having coding knowledge are also welcome to enroll in a preparatory program. 

You can also check out the Hero Vired Integrated Program in Data Science, Machine Learning, and Artificial Intelligence which is crafted for those having a bachelor’s degree and a background in mathematics and coding. This course is particularly tailored for science undergrads with an exclusive curriculum in programming, smart technologies, and predictive analysis. The integrated program aims for its learners to achieve solid expertise in analyzing big data, distributive computing, and other machine learning concepts.