Don’t Get Fired, Join These Courses and Prepare for Future AI Job

Last Updated on November 13, 2023 by SPN Editor

Several IT companies are downsizing their workforce in response to the rapid evolution and integration of Artificial Intelligence (AI) Job. Prominent IT players such as Microsoft, Meta, Google, Amazon, and Twitter have initiated workforce reductions, affecting members of their “responsible AI job teams.”

Challenger, Gray & Christmas, an outplacement firm, disclosed that 3,900 individuals were laid off in May due to sudden demands in AI job, marking the first instance of job cuts specifically attributed to this factor.

IBM is strategically leveraging AI to replace around 7,800 jobs over the next five years. Arvind Krishna, the company’s CEO, clarified that the roles being replaced predominantly involve non-customer-facing positions, including back-office functions such as HR. This approach aims to streamline operations and enhance efficiency.

Even startups are not immune to this transformative wave. The Indian startup Dukaan reported a substantial reduction in its workforce. CEO Summit Shah revealed that 90% of support staff has been replaced by an AI chatbot, leading to a remarkable 85% cost reduction in the company’s customer support function.

While these developments understandably raise concerns about AI job security in the tech sector, some industry leaders posit that AI will ultimately create more jobs than it eliminates. The ongoing evolution of AI is expected to bring further changes to the tech industry, potentially resulting in a redefinition of the types of roles and skills in demand.

Investing in learning and upskilling is a prudent strategy to secure AI job in the midst of cutting workforces, particularly in the dynamic and impactful field of Artificial Intelligence (AI). With a broad range of applications, AI stands as a rapidly growing field, creating a heightened demand for skilled professionals.

How can you prepare for the impact of an AI Job?

While Artificial Intelligence (AI) is anticipated to replace certain jobs, it is equally expected to generate new employment opportunities. By cultivating relevant skills and adapting to the evolving job market, you can not only navigate the era of AI but also capitalize on the opportunities it brings.

Preparing ongoing learning and staying attuned to the latest industry developments are essential strategies for thriving in this AI era. The ability to leverage AI-related skills positions individuals to contribute meaningfully to emerging fields and sectors, ensuring they remain agile and competitive in the evolving AI job market shaped by AI technologies.

Machine Learning

Defined as the science of enabling computers to learn and mimic human behavior, machine learning empowers systems to autonomously improve over time. This is achieved by feeding them data and information, observed through real-world interactions.

Deep Learning

A subset of machine learning, deep learning involves neural networks—algorithms inspired by the human brain. These networks learn from extensive datasets, facilitating intricate pattern recognition and complex problem-solving.

Natural Language Processing (NLP)

NLP endows a computer program with the ability to understand human language as it is spoken. Its applications are diverse, encompassing tasks such as translation, entity recognition, sentiment analysis, and more.

Computer Vision

This field revolves around methods for acquiring, processing, analyzing, and understanding digital images or video. Computer vision’s goal is to extract high-dimensional data from the real world, producing numerical or symbolic information.

Reinforcement Learning:

An integral aspect of machine learning, reinforcement learning involves an agent learning to behave in a given environment. This learning process is facilitated by the agent performing specific actions and observing the outcomes.

Opportunities for AI Job Seekers

The demand for AI jobs is substantial, presenting individuals with a wide array of growth opportunities within the field. Below are some high-demand and ever-evolving roles for AI Job Seekers

Software Engineer

Professionals in this role blend principles from computer science, engineering, and mathematics to create and test software applications on computer devices.

Data Scientist

This role involves extracting valuable insights from extensive datasets. Data scientists necessitate a robust understanding of statistics and programming to analyze and interpret data effectively.

Software Development Engineer

These professionals are tasked with designing, developing, and maintaining software systems, contributing to the continuous evolution of technological solutions.

Research Scientist

Engaging in AI-focused research, these individuals employ diverse resources to collect data and contribute to the advancement of AI projects.

User Experience Designer

UX designers play a crucial role in crafting and implementing features within digital tools, ensuring optimal user experiences and interactions.

AI Engineer

AI engineers interpret business and market trends, process raw data, construct AI tools, and leverage data science methodologies to gain a competitive advantage.

Natural Language Processing Engineer

Professionals in this role work on systems that enable machines to comprehend and process human language, contributing to advancements in natural language understanding.

Machine Learning Engineer

Responsible for designing and implementing machine learning systems or software, these engineers play a pivotal role in developing AI-driven solutions.

Computer Vision Engineer

Engineers specializing in computer vision work on enabling machines to interpret and understand the visual world, contributing to advancements in image and video analysis.

Business Professionals, Managers, Science and Engineering Professionals, Legal, Social and Cultural Professionals

These roles, spanning various sectors, have been significantly influenced by AI advancements and automation, emphasizing the widespread impact of AI across industries.

Educational Qualification Required to Get an AI Job

Becoming an AI expert can significantly vary based on your current educational background, programming experience, and knowledge of statistics and data science. Here are some general common educational qualifications to secure a lucrative AI Job:

Bachelor’s Degree in AI

Pursuing a college degree in AI typically takes around four years for full-time students. This comprehensive program provides in-depth training in AI and related subjects, laying a solid foundation for understanding the field.

Mastering a Craft

Research indicates that it takes approximately 10,000 hours to master any craft. This benchmark can be particularly useful for those planning to engage in self-study, emphasizing the dedication required to achieve proficiency in AI.

Online Certificates

For those seeking more flexible and focused learning paths, guided projects within online certificates can be completed in as little as an hour. However, many certificate programs may span up to six months of dedicated time. Additionally, some platforms offer degree programs that take 2-4 years to complete, providing a more comprehensive education in AI.

Self-Study

The duration for acquiring the basics of AI through self-study can vary. Some individuals may grasp the fundamentals in a few weeks or months, while others might require several years of study and practical experience to become proficient. The self-study approach allows for flexibility in pacing one’s learning journey based on individual capabilities and commitments.

Take Opportunities from Free Online Courses on AI

Numerous free online courses are available to facilitate learning in the field of Artificial Intelligence (AI). Here are some notable platforms offering such courses which would help you to secure an AI job:

Udemy

Udemy offers a diverse range of free courses on Artificial Intelligence, providing learners with the opportunity to explore various aspects of this dynamic field.

Great Learning

Great Learning provides free courses on AI, and upon successful completion, learners can receive a certificate. This platform offers a structured and comprehensive approach to AI education.

Tech.co

Tech.co has compiled a curated list of the best free AI training courses. This resource serves as a valuable guide for individuals seeking high-quality and accessible AI education.

Elements of AI

“Elements of AI” presents a series of free online courses developed by MinnaLearn and the University of Helsinki. This series covers fundamental concepts in AI, making it an excellent starting point for learners at various levels.

Enrol in Professional Courses from Reputed Institutions

If you want to pursue a full-time course and learn AI from the reputed Institutions, you can try admission in these selected Institutes. For data scientists seeking to enhance their expertise in Artificial Intelligence (AI), the following courses offer valuable insights and advanced training:

DeepLearning.AI Advanced Learning Algorithms Course (University of Toronto)

This course delves into learning algorithms, a crucial aspect of data science. Developed by DeepLearning.AI and the University of Toronto, it provides a deep understanding of these algorithms, enhancing the skill set of data scientists.

Machine Learning on Google Cloud (Udacity)

Focused on the implementation of machine learning models using Google Cloud, this Udacity course is tailored for data scientists. Google Cloud is a prominent platform in the field of data science, making this course particularly relevant for those looking to apply machine learning in cloud environments.

Advanced Machine Learning with TensorFlow on Google Cloud Platform (Google Cloud Training)

TensorFlow, a popular framework for creating machine learning models, takes center stage in this advanced training course offered by Google Cloud Training. Data scientists can gain insights into advanced machine learning techniques within the Google Cloud Platform.

MLOps (Machine Learning Operations) Fundamentals (Google Cloud Training)

This course covers the fundamentals of MLOps, a critical aspect of deploying and managing machine learning models. Understanding MLOps is essential for data scientists involved in the operational aspects of machine learning.

ML Pipelines on Google Cloud (Google Cloud Training)

Focusing on building machine learning pipelines, this course from Google Cloud Training is tailored for data scientists. Machine learning pipelines are instrumental in automating the workflow and streamlining processes for efficient model development and deployment.

Advanced Certification in Data Science and AI (IIT Madras)

Offered by IIT Madras, this comprehensive certification covers a spectrum of tools and technologies in Data Science, Machine Learning, Deep Learning, and Artificial Intelligence. It provides data scientists with a well-rounded understanding of key concepts in the field.

These courses span a diverse range of topics, from fundamental machine learning algorithms to advanced cloud-based implementations. They offer a solid foundation for data scientists aiming to broaden their knowledge in AI, emphasizing the importance of a robust grasp of mathematics and programming for success in the field.