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Course Description
The abbreviation Artificial Intelligence (AI) has been named the Collins Word of the Year for 2023, the dictionary publisher said on 31st October 2023. "AI for All" is a meticulously crafted educational program tailored for individuals new to the field of AI but passionate about learning. This comprehensive course provides beginner-friendly training, introducing learners to fundamental concepts and terminology in Artificial Intelligence, Machine Learning, Data Science, Deep Learning, and AI Tools.
Objectives
The program addresses important considerations like avoiding pitfalls and guides participants on their journey to undertaking AI projects and fostering effective team building.
Audience
AI is no longer limited to just engineers. The course "AI for All" offers a non-technical approach, focusing on enabling individuals to comprehend AI technologies and identify opportunities to apply AI within their own organizations. The course illustrates real-life examples to showcase the current capabilities and limitations of AI. Furthermore, participants will gain insights into the impact of AI on society and learn how to navigate through this technological revolution.
For non-technical business professionals, "AI for All" helps in devising a sustainable AI strategy. On the other hand, if you are a machine learning engineer or data scientist, this course is designed specifically for you to encourage your manager, VP, or CEO to gain a comprehensive understanding of what you can achieve (and what you cannot) with AI.
Prerequisites
This program is not only engineers but for anyone from diverse backgrounds who aspire to develop their careers in AI or enhance their organization's utilization of AI technologies.
Content
1. Introduction to AI
a. What is Artificial Intelligence
b. Brief History of AI
c. Types of AI
d. Applications of AI
2. Major Components of AI
a. Machine Learning
a.1. What is Learning
a.2. Why do we need Machine Learning?
a.3. Types of learning
a.4. Relations to other fields
b. What machine learning can and cannot do
3. Principles of AI
a. The Data
b. The Algorithms
4. Fields of AI
b. NLP
c. Robotics
d. Computer Vision
5. Neural Networks and Deep Learning
a. Artificial Neural Networks
b. What’s Deep Learning all about
c. Understanding images
d. non-technical explanation of Deep Learning
6. The Projects of AI
a. Recognise Machine Learning Project
b. Workflow of Data Science
c. Example of an AI project
7. Where you will Fit
a. Framing an AI team
b. Example role of an AI team
b. Tools useful for AI teams
8. AI and It’s Culture
a. Partnering with AI
b. AI pitfalls to avoid
c. Fear of AI
9. AI and It’s Community
a. Civilization view of AI
b. Discrimination/Bias
c. Our Role in Different stage of AI
10. AI momentum
a. Success Stories of AI in India and other parts of the world
b. Jobs you can look out for
What does a non-technical AI knowledgeable person can do in an AI driven world?
Identify AI opportunities: Non-technical individuals can explore and identify areas within their organization or industry where AI technologies can be effectively applied. This could involve recognizing processes or tasks that are time-consuming or repetitive and suggesting AI solutions to automate or optimize them.
AI strategy and leadership: Non-technical professionals can play a crucial role in developing an AI strategy for their organization. By understanding the potential impact of AI on business operations, they can contribute to decision-making processes and provide insights into how AI can be integrated into existing workflows.
Ethical considerations: Ethical implications are a significant aspect of AI adoption. Non-technical individuals can contribute to discussions around AI ethics, privacy concerns, and social impacts. Their perspectives can help shape policies and guidelines to ensure responsible and ethical use of AI technologies.
Collaborate with technical experts: Non-technical individuals can collaborate with technical teams, including data scientists and AI engineers, to define requirements, communicate objectives, and bridge the gap between business needs and technical implementations. Effective cross-functional collaboration is essential for successful AI projects.
Continuous learning: While non-technical professionals may not need to know intricate technical details, they can still benefit from continuous learning about AI concepts, trends, and advancements. This knowledge enables them to stay informed and adapt to the ever-evolving AI landscape.
Remember, even without technical expertise, individuals can contribute their unique perspectives, critical thinking, and domain knowledge to navigate and leverage the potential of AI in their respective fields.
What are the domains where a non-technical AI knowledgeable learner can work?
In non-technology domains, non-technical AI learners can explore career opportunities in areas such as:
Healthcare: Non-technical AI learners can work on projects related to AI-driven diagnostic tools, patient monitoring systems, or health data analysis.
Finance: They can contribute to AI applications in fraud detection, credit risk assessment, or algorithmic trading.
Agriculture: Non-technical AI learners can explore the use of AI in precision agriculture, crop yield prediction, or pest monitoring.
What are the domains where a technical/non-technical AI knowledgeable learner can work?
In technology domains, non-technical AI learners can find employment in roles that involve leveraging AI technologies to solve business challenges. Some potential areas include:
AI Implementation and Project Management: Non-technical AI learners can manage and oversee AI projects, ensuring successful implementation and alignment with business goals.
AI Strategy and Consulting: They can contribute to developing AI strategies and advising companies on how to integrate AI into their operations.
AI Sales and Marketing: Non-technical AI learners can work in sales and marketing roles, promoting and educating customers about AI solutions.
Top Job Roles for an AI Associate beginners (Non-Technical)
According to an article from Forbes, there are several AI-related jobs for non-technical individuals, including:
AI Product Manager: responsible for defining the product strategy, working with cross-functional teams, and identifying AI opportunities.
AI Sales and Marketing Specialist: responsible for evangelizing AI solutions, generating leads, and collaborating with sales and marketing teams.
AI UX Designer: responsible for designing AI systems with intuitive and human-friendly interfaces.
AI Technical Writer: responsible for creating documentation, user guides, and other materials with a technical focus that help end-users understand AI applications.
AI Business Development Manager: responsible for identifying potential AI partnerships, managing the negotiation process, and developing and nurturing long-term business relationships.
AI Ethicist: responsible for identifying and addressing ethical concerns related to AI technologies in different domains like healthcare, finance and agriculture.
Prompt Engineer: Responsible for developing conversational AI for chatbots, websites, and mobile applications.
Recommender System Specialist: Responsible for building and updating algorithms that suggest content, products, and services to users on websites and applications.
Data Analyst: Responsible for interpreting data for businesses to uncover insights into customers, markets, and competitors. AI training could be a useful addition to this skillset.
Top Job Roles for an AI Associate - beginners (Technical)
Here are some top job roles for a technical entry-level AI learner:
AI Engineer: An AI Engineer is responsible for designing and building AI systems using programming languages such as Python, R or Java.
Machine Learning Engineer: A Machine Learning Engineer focuses on training and deploying Machine Learning models by using specific algorithms and data analysis.
AI Research Scientist: An AI Research Scientist is involved in computer science research to develop new machine learning and AI techniques.
Data Scientist: A Data Scientist is responsible for discovering and analysing complex data sets using machine learning algorithms, statistical models, and predictive analytics.
Robotics Engineer: A Robotics engineer integrates AI algorithms and software to develop robotics systems that can perform complex tasks.
These roles require technical skills such as programming, data analysis, machine learning, and mathematics. Entry-level AI learners who are technical can explore these roles by developing practical skills in these areas.
Salary of an AI Engineer (Technical & Non- Technical) in India.
The starting salary for freshers in AI in India is around Rs. 6 LPA and can stretch up to Rs. 12 LPA.
Is it worth to pursue a career in AI engineer?
The Indian AI market is expected to experience significant growth in the coming years, reaching a staggering value of $435.0 billion by 2025. With such a substantial presence of skilled professionals, India is well positioned to capitalize on this opportunity and become a key player in the AI industry. The surge in demand for AI professionals has also been fuelled by the increasing investment in AI research and development by both private companies and the government. As a result, there is a scarcity of skilled AI professionals in the country, leading to fierce competition among organisations to hire top talent. The demand for AI specialist is not limited to the IT sector alone, but extends to fields such as healthcare, finance, manufacturing, and retail.
Considering the growth demand for AI professionals and the promising future of the Indian AI industry, pursuing a career in AI in India can be a wise decision.