The document provides information about career opportunities in artificial intelligence. It discusses various applications of AI across industries like healthcare, entertainment, banking/finance, marketing, retail, manufacturing and more. It outlines popular job roles in AI like software engineers, data scientists, AI researchers, intelligence specialists, consultants, AI data analysts, machine learning engineers, sales engineers, and product managers. The document also provides sample job descriptions for roles like artificial intelligence engineer and machine learning engineer. It discusses necessary skills for AI careers like Python, Java, R, machine learning frameworks, data science, analytics and more. Finally, the document shares success stories from the Post Graduate Program in Artificial Intelligence and Machine Learning (PGP-AIML).
Summary artificial intelligence in practice- part-2GMR Group
Burberry uses customer data from loyalty programs and social media to offer personalized recommendations and product suggestions to customers in its stores. Sales assistants use tablets that provide information on customer purchase histories to recommend complementary products. Burberry aims to replicate the personalized experience of online shopping in its physical stores. Coca-Cola analyzes large amounts of customer data from sales and feedback to inform business decisions. It has developed new products like Cherry Sprite based on analysis of customer drink mixtures at self-service fountains. Coca-Cola is also using AI in product development, health initiatives, augmented reality applications, and social media analysis.
How To Identify The Best AI Opportunities For Your Business – In 2 Simple Steps Bernard Marr
Artificial Intelligence (AI) is the biggest and most transformative technology trend of our time. Every business, big or small, will have to consider the impact of AI on their organization. Here we look at how you do this in practice.
Summary artificial intelligence in practice- part-4GMR Group
American Express uses machine learning to detect credit card fraud and improve the customer experience. Models analyze transaction data and cardholder information to identify suspicious activity within milliseconds. This has saved millions by reducing fraudulent transactions. Elsevier applies AI to medical literature and patient data to generate personalized treatment pathways and improve outcomes. Entrupy develops scanning technologies using computer vision and deep learning to identify counterfeit goods with 98.5% accuracy, helping brands combat the $450 billion counterfeit industry.
1) Integrating artificial intelligence with the Internet of Things provides advantages like managing risk more effectively, improving existing products and services, and gaining insights from data analytics.
2) AI and IoT are increasingly being used together, with IoT devices generating data that can then be analyzed using AI/ML to identify patterns and anomalies.
3) Examples of AI-embedded IoT include using robots in factories, facial recognition in retail stores, remote patient monitoring technologies, and optimizing transit systems.
Beyond the Buzz: How Sectors as Diverse as Logistics, Finance, Healthcare & M...Leah Kinthaert
In their report, “Predictions 2017: Artificial Intelligence Will Drive The Insights Revolution”, Forrester Research predicts that “insights-driven businesses will steal $1.2 trillion per annum from their less-informed peers by 2020”. Statista tells us that this year “the global AI market is expected to be worth approximately 7,35 billion U.S. dollars.”
I compiled a “best of” e-book for Informa Connect Learning from interviews with 34 pioneers on the topic of AI in marketing, healthcare, finance and maritime/logistics. From Wolfgang Lehmacher, Head of Supply Chain and Transport Industries of the World Economic Forum to Forbes 30 under 30 Domeyard Hedge Fund Partner, Christina Qi, the Global No. 1 Fintech, AI,
Blockchain & No. 2 InsurTech Influencer by Onalytica, Spiros Margaris to award winning scientist and entrepreneur, ReviveMed CEO and Co-Founder, Leila Pirhaji -
learn how 34 of the top artificial intelligence experts in the world are using AI to disrupt their industries, increase profits, drive efficiencies and in many cases - save lives.
Artificial intelligence is becoming increasingly important for businesses. It can automate tasks like customer service, improve marketing through personalized experiences, and help predict outcomes. As more companies develop new AI technologies, those that don't adopt AI may struggle to keep up with competitors in terms of productivity and efficiency. The document provides several examples of how businesses are using AI for tasks like operational automation, predictive maintenance, fraud prevention, and more. It concludes that AI offers businesses many benefits and opportunities for growth.
The fashion industry is integrating AI to improve various aspects of design, manufacturing, supply chain management, and customer experience. AI is being used to help customize products to individual customer preferences and analyze trends. Brands are partnering with AI companies to better understand customer sentiment and identify popular styles/themes. Algorithms are also improving demand forecasting, inventory management, and logistics to increase efficiency. Chatbots and virtual fitting tools provide personalized recommendations to customers.
Disrupting Reality: Taking Virtual & Augmented Reality to the EnterpriseCognizant
The impact of virtual and augmented reality platforms and applications will be profound for enterprises across industries, allowing companies to transform processes and improve how employees work, communicate and collaborate. All within a real-time, "real-life" environment that reduces the need for physical premises and presence.
ROBOTS AND HUMANS: COMBINED CAPABILITY WILL ENABLE BUSINESSES DELIVER UNEXPEC...VARUN KESAVAN
The last few years have seen a significant infusion of robots in various industries. This trend is expected to continue in the next 3-5 years. Almost 1 million robots are expected to be sold for enterprise use in 2020. There are primarily 3 types of robots - industrial, professional services and software robots.
Professional service robots (e.g., those used in healthcare, retail industries) and software robots (e.g., those used in functions such as Finance, HR, Procurement) will comprise a significant portion of these new robot sales. The market for professional services and software robots is growing much faster than that for industrial robots.
As the use of robots, increase in non-manufacturing industries, the companies which are able to combine the uniquely native human capabilities (e.g., inspiration, aspiration, emotion, empathy, imagination) with powerful robot capabilities (e.g., accurate transaction processing) will be able to re-imagine their business processes and deliver better and newer business outcomes for their stakeholders.
Term paper on role of e commerce in indiaSubhadeep Roy
E-commerce in India has grown rapidly in recent years and is expected to continue growing significantly. E-commerce revenue in India is projected to increase from $30 billion in 2016 to $120 billion by 2020, representing the highest annual growth rate in the world. Key drivers of growth include rising internet and smartphone penetration, a young demographic, and increasing adoption of online shopping. Several industries are also being impacted, including technology, logistics, travel, and retail. The rapid growth of the e-commerce sector is expected to further transform the Indian economy and drive innovation across many industries.
Ai in retail sales and crm venkat vajradhar - mediumvenkatvajradhar1
Artificial intelligence in the retail sector is being applied in new ways, from the whole product and service cycle to assembly-to-post customer service interactions, but the key questions for retail players.
Indian Unicorns will continue to strengthen through acquisitions in Mobile, M...ProductNation/iSPIRT
With Mergers and Acquisitions (M&A) totaling $2.27bn since Jan 2011, technology majors as well as large Indian ‘Unicorns’ are likely to continue acquiring Indian Technology product startups to fill technology gaps as well as talent requirements. This was among the key trends to emerge from the Think Next Roundtable Report - 2015 India technology Product M&A Industry Monitor Report released by iSPIRT, India’s software products think tank, technology focused M&A advisory boutique Signal Hill and Microsoft Ventures.
6 Ways To Use Artificial Intelligence In Your Businessvenkatvajradhar1
Artificial Intelligence (AI) has long been seen as a vicious entity, dead to exterminate humanity, or at least, to keep its members out of commission. However, artificial intelligence is far from it, which brings us to the question: What is AI?
How is AI improving customer experience in Retail?Juliana Vectore
This document provides an overview of an MBA project examining how AI is improving the customer experience in retail. It includes definitions of AI, a mapping of key AI technologies and applications in retail, an assessment of the applications' benefits and maturity levels, and benchmarks of AI adoption by retailers Alibaba, Walmart and Sephora. The project finds that AI has significant potential to enhance the customer experience, especially in e-commerce, and that retailers' investment priorities are driven by their goals of providing unique experiences or value.
E-commerce is expected to grow significantly in Asia in the coming years, with the number of digital buyers in Asia Pacific projected to exceed 1 billion by 2018. In India specifically, active e-commerce penetration is currently only 28% but is expected to increase substantially given India's growing internet user base and trends toward online shopping. The e-commerce market in India grew from $2.5 billion in 2009 to an estimated $38.5 billion by 2017. Major types of e-commerce include business-to-business, business-to-customer, business-to-government, and consumer-to-consumer. The future of e-commerce in India is promising due to increasing demand for broadband access, rising living standards,
The Robot and I: How New Digital Technologies Are Making Smart People and Bus...Cognizant
Our latest study shows that when enterprise robots are applied to automating core business processes, they can extend the creative problem-solving capabilities and productivity of human beings and deliver superior business results.
'Converge' Report - Shaping Artificial Intelligence for Southeast AsiaShu Jun Lim
This document provides an overview of artificial intelligence and how startups in Southeast Asia are applying AI. It discusses how startups are collecting local training data to build AI solutions that understand Southeast Asian contexts. It also explores how startups are developing natural language processing for local languages and building chatbots on popular regional messaging platforms. Additionally, it examines how other startups are using AI and automation to digitize field operations and business processes.
20 Useful Applications of AI Machine Learning in Your Business ProcessesKashish Trivedi
A 2017 study from Pew Research found that more than 70% of the U.S. is scared that robots are going to take over our lives. And, while we can’t perfectly predict the emergence of a Skynet singularity, we can say with some certainty that technology is set to take over the repetitive, dehumanizing elements of our jobs instead of putting us out of work. Artificial intelligence (AI) is a strategic priority for 84% of businesses, and in some cases has been used to improve sales team efficiency by over 50%. Even I’ve used AI in the past to generate hundreds of relevant hashtags for social media posts at the click of a button. It was once the stuff of utopian science fiction and huge enterprises, but now practically anyone can take advantage. For this post, we will dive into 20 different applications of AI in the real world.
20 Useful Applications of AI Machine Learning in Your Business ProcessesKashish Trivedi
The fear of robots taking over our lives has been a prevalent concern, with over 70% of the U.S. population expressing apprehension, as highlighted by a 2017 Pew Research study. However, while the emergence of a Skynet-like scenario remains uncertain, it's evident that technology, particularly artificial intelligence (AI), is poised to revolutionize various aspects of our daily tasks, freeing us from repetitive and dehumanizing job elements rather than rendering us obsolete. With AI being a strategic priority for 84% of businesses, its implementation has shown remarkable efficiency enhancements, such as boosting sales team productivity by over 50%. The accessibility of AI tools has expanded significantly, enabling practically anyone to leverage its benefits. In this discourse, we'll explore 20 diverse real-world applications of AI, ranging from healthcare and finance to entertainment and government, illustrating its pervasive impact on modern society.
A Guide on How AI Contributes to Businesses in Today’s Era to Watch in 2023.Techugo
Artificial Intelligence and Machine Learning have become the main focus of the scene. Artificial intelligence can be used for a wide variety of uses in business, including streamlining processes and aggregating the performance of companies. Researchers are still determining what AI will mean for businesses shortly. AI is predicted to shift technological advancement away from the traditional two-dimensional screen and towards the three-dimensional physical space surrounding the person.
Although the acceptance by society in general for AI does not mean anything new. The idea itself isn’t. Artificial intelligence is a broad field of business application. Indeed, most of us interact with AI in some way or another. Artificial Intelligence is changing all aspects of business across every industry. To know more, visit the post.
AI & Analytics Predictions of 2022. InfographicInData Labs
What does 2022 hold for artificial intelligence? Will the AI revolution continue to gain momentum?
This report will provide a look into the future of AI technologies, including:
- Strategic AI predictions and trends for 2022 and beyond
- The current and projected state of the AI market and its value
- Business functions that already benefit from AI implementation
- Industries where AI is making the greatest disruption
- The business value generated by Artificial Intelligence
- Costs of AI implementation and main challenges
Gartner predicts that in 2020, organizations using AI tech will achieve long-term success 4 times more than others. Considering the exponential expansion and influence of AI and its exceptional value, adopting this technology is no longer a choice, but a need, for organizations.For more visit at https://www.payjo.co/blog/13-reasons-why-your-business-needs-ai/
Evolution of AI ML Solutions - A Review of Past and Future Impact.pdfChristine Shepherd
Need to incorporate technologies that drive unparalleled advancements? If yes, leveraging AI and Machine Learning services helps enterprises to streamline operations and also usher in a new era of possibilities and societal benefits. Whether it's designing novel solutions, creating intelligent products, or optimizing workflows, AI and ML serve as catalysts for innovation, propelling enterprises into the forefront of their respective industries.
Gartner predicts that in 2020, organizations using AI tech will achieve long-term success 4 times more than others. Considering the exponential expansion and influence of AI and its exceptional value, adopting this technology is no longer a choice, but a need, for organizations.
Here are 13 reasons why your business needs AI:
In 2023, AI will turbocharge your tactics for digital transformation.Sun Technologies
Artificial intelligence is a formidable technology that can help you accelerate your digital transformation.
Businesses are becoming increasingly data-driven due to digitalization, which enables smooth access to everything. This has enabled businesses to use cutting-edge technologies to make better decisions.
Artificial intelligence (AI), also known as machine intelligence, is an aspect of computer science that deals will the designing of intelligent mechanical systems that work and react like humans. AI incorporates information from everything ranging from Google search algorithms to machinal processes. From SIRI to self-driving cars, everything is the outcome of artificial intelligence, which is rapidly progressing and taking over our human lives.
Artificial Intelligence (AI) is a transformative technological paradigm that empowers machines to
simulate human-like cognitive functions. At its core, AI aims to equip machines with the ability to
learn, reason, and make decisions independently, mirroring human intelligence.
Artificial Intelligence has been around for almost 70 years, but only in recent years has it become a major disrupter for many industries due to the convergence of big data, processing power and cloud computing. This has led to the development of “deep learning”, which allows a type of computer intelligence that closely mimics human decision-making. In this paper, I take look at the evolution of Artificial Intelligence, along with two disparate industries: Retail and Real Estate. These industries have adopted AI at different speeds. Also, each industry has its own form of resistance and uses for the technology. My theory is that there are forms of technology resistance by major players in the real estate industry in combination with the long industry cycles that are causing slow adoption.
Artificial Intelligence can Offer People Great Relief from Performing Mundane...JPLoft Solutions
AI refers to the recreation of human-like intelligence in machines created to function like humans and mimic their actions. Artificial Intelligence solutions can be applied to any device that exhibits traits similar to the human brain, such as the capacity to learn and analytical thinking.
AI and Marketing: Robot-proofing Your JobCall Sumo
Artificial Intelligence (AI) provides marketers with deep knowledge of consumer, clients and delivers the right message to the right person at the right time. Here are more depth information how AC affects on Marketing.
Artificial intelligence Trends in MarketingBasil Boluk
This document provides an overview and summary of key insights about artificial intelligence (AI) adoption from various research reports:
- Investment in AI remains high but large-scale adoption is happening slowly, as many companies are still in the planning phases.
- Research forecasts strong growth in the global AI market size over the next few years, reaching $60 billion by 2025, though most investment still comes from large tech companies.
- Adoption of AI technologies varies by industry, with around 20% of companies surveyed having adopted at least one AI technology at scale so far, while others are still experimenting or planning adoption.
With enterprises putting digital at the core of their transformation, our annual Data Science & AI Trends Report explores the key strategic shifts enterprises will make to stay intelligent and agile going into 2019. The year was marked by a series of technological advances, including advances in AI, deep learning, machine learning, hybrid cloud architecture, edge computing (with data moving away to edge data centres), robotic process automation, a spurt of virtual assistants, advancements in autonomous tech and IoT.
Data Science & AI Trends 2019 By AIM & AnalytixLabsRicha Bhatia
This document discusses 10 data science and AI trends to watch for in India in 2019. It begins with an executive summary noting that enterprises are putting digital technologies like AI, machine learning, and analytics at the core of their transformations. It then discusses each of the 10 trends in more detail, with quotes from experts about how each trend will impact industries and businesses. The trends include more industries utilizing analytics and AI, deploying models for real-time use cases, using data analysis for informed customer engagement, increasing investment in data infrastructure, analytics becoming more pervasive, the need for greater collaboration, personalized products, making analytics more human-centric, replacing centralized data with a single customer view, and the growth of voice and AI assistants.
In today's tech-centric world, choosing the right AI development partner is crucial. Companies like DataRoot Labs, AssemblyAI, and Element AI highlight the enduring importance of AI-industry collaboration, driving innovation in sectors from healthcare to environmental sustainability. AI is no longer optional; it's essential for forward-thinking organizations. In 2023, these companies and trends provide a roadmap for those aiming to lead in the AI frontier.
In recent years AI and ML capabilities have advanced exponentially, blurring the line between fantasy and reality, thus creating an unparalleled market opportunity for whoever can bring the technology to eager consumers.
Today there is an abundance of demand for more intelligent and human-like behavior and technology on the market, and now we have concrete ways to fill that demand. Everybody’s playing, but only some will strike it rich.
This edition is an exploration on how to incorporate AI to products and services in a very real and organic way. Dive in and let’s take a look!
Similar to ARTIFICIAL INTELLIGENCE & MACHINE LEARNING CAREER GUIDE (20)
This document outlines a plan to present on exploratory data analysis using the Python libraries dataprep.eda and pandas-profiling. The presentation will cover the data analytics life cycle, exploratory data analysis, how to install and use the two libraries, and conclusions. Sections are dedicated to exploring EDA using Python libraries in general as well as specifically focusing on the installation and use of dataprep.eda and pandas-profiling.
This document provides an introduction to data science. It discusses the rapid growth of data and defines data science as extracting insights from vast amounts of data using scientific methods. The document outlines the typical steps in the data science process: acquire, prepare, analyze, report and act on data. It also discusses career opportunities in data science and common tools used, including programming languages, mathematics/statistics foundations and visualization/modeling tools.
This document provides a summary of various cheat sheets for AI topics including neural networks, machine learning, deep learning, and big data. It includes sections on neural network basics and graphs, machine learning basics and algorithms, and data science tools and libraries like TensorFlow, PyTorch, NumPy, Pandas, and Matplotlib. The document aims to be a complete list of the best AI cheat sheets for readers to learn key concepts in a concise manner.
1) The document discusses using machine learning and AI in banking and finance, specifically for a case study on a Tunisian bank (STB Bank).
2) It outlines several potential use cases for machine learning in areas like credit scoring, fraud detection, customer sentiment analysis, risk management, and operational efficiency.
3) The methodology discussed follows a CRISP process involving business understanding, data understanding, data preparation, modeling, evaluation, and deployment with feedback.
Linear regression is a machine learning algorithm that models the relationship between independent variables (x) and a continuous dependent variable (y). It finds the best fit linear equation to model the relationship.
Multiple linear regression extends this to model relationships between a continuous dependent variable and two or more independent variables. The model represents the predicted output as a linear combination of the input variables.
Gradient descent is an optimization algorithm used to minimize some function by iteratively moving in the direction of steepest descent as defined by the negative of the gradient. It can be used to learn the parameters of a linear regression model by minimizing the cost function, which represents the error between predictions and true values. Feature scaling helps ensure features are on a similar
The document discusses decision tree models in machine learning. It begins by defining key terms like decision nodes, branches, and leaf nodes. It then explains how decision trees are built in a top-down manner by recursively splitting the training data based on selected attributes. The document also covers different algorithms for building decision trees like ID3, C4.5, and CART. It discusses measures used for attribute selection like information gain, gain ratio, and Gini index. Finally, it provides an example of how to build a decision tree to classify whether to play tennis based on weather attributes.
PRESS RELEASE - UNIVERSITY OF GHANA, JULY 16, 2024.pdfnservice241
The University of Ghana has launched a new vision and strategic plan, which will focus on transforming lives and societies through unparalleled scholarship, innovation, and result-oriented discoveries.
Benchmarking Sustainability: Neurosciences and AI Tech Research in Macau - Ke...Alvaro Barbosa
In this talk we will review recent research work carried out at the University of Saint Joseph and its partners in Macao. The focus of this research is in application of Artificial Intelligence and neuro sensing technology in the development of new ways to engage with brands and consumers from a business and design perspective. In addition we will review how these technologies impact resilience and how the University benchmarks these results against global standards in Sustainable Development.
Codeavour 5.0 International Impact Report - The Biggest International AI, Cod...Codeavour International
Unlocking potential across borders! 🌍✨ Discover the transformative journey of Codeavour 5.0 International, where young innovators from over 60 countries converged to pioneer solutions in AI, Coding, Robotics, and AR-VR. Through hands-on learning and mentorship, 57 teams emerged victorious, showcasing projects aligned with UN SDGs. 🚀
Codeavour 5.0 International empowered students from 800 schools worldwide to tackle pressing global challenges, from bustling cities to remote villages. With participation exceeding 5,000 students, this year's competition fostered creativity and critical thinking among the next generation of changemakers. Projects ranged from AI-driven healthcare innovations to sustainable agriculture solutions, each addressing local and global issues with technological prowess.
The journey began with a collective vision to harness technology for social good, as students collaborated across continents, guided by mentors and educators dedicated to nurturing their potential. Witnessing the impact firsthand, teams hailing from diverse backgrounds united to code for a better future, demonstrating the power of innovation in driving positive change.
As Codeavour continues to expand its global footprint, it not only celebrates technological innovation but also cultivates a spirit of collaboration and compassion. These young minds are not just coding; they are reshaping our world with creativity and resilience, laying the groundwork for a sustainable and inclusive future. Together, they inspire us to believe in the limitless possibilities of innovation and the profound impact of young voices united by a common goal.
Read the full impact report to learn more about the Codeavour 5.0 International.
How to Manage Line Discount in Odoo 17 POSCeline George
This slide will cover the management of line discounts in Odoo 17 POS. Using the Line discount approach, we can apply discount for individual product lines.
APM event held on 9 July in Bristol.
Speaker: Roy Millard
The SWWE Regional Network were very pleased to welcome back to Bristol Roy Millard, of APM’s Assurance Interest Group on 9 July 2024, to talk about project reviews and hopefully answer all your questions.
Roy outlined his extensive career and his experience in setting up the APM’s Assurance Specific Interest Group, as they were known then.
Using Mentimeter, he asked a number of questions of the audience about their experience of project reviews and what they wanted to know.
Roy discussed what a project review was and examined a number of definitions, including APM’s Bok: “Project reviews take place throughout the project life cycle to check the likely or actual achievement of the objectives specified in the project management plan”
Why do we do project reviews? Different stakeholders will have different views about this, but usually it is about providing confidence that the project will deliver the expected outputs and benefits, that it is under control.
There are many types of project reviews, including peer reviews, internal audit, National Audit Office, IPA, etc.
Roy discussed the principles behind the Three Lines of Defence Model:, First line looks at management controls, policies, procedures, Second line at compliance, such as Gate reviews, QA, to check that controls are being followed, and third Line is independent external reviews for the organisations Board, such as Internal Audit or NAO audit.
Factors which affect project reviews include the scope, level of independence, customer of the review, team composition and time.
Project Audits are a special type of project review. They are generally more independent, formal with clear processes and audit trails, with a greater emphasis on compliance. Project reviews are generally more flexible and informal, but should be evidence based and have some level of independence.
Roy looked at 2 examples of where reviews went wrong, London Underground Sub-Surface Upgrade signalling contract, and London’s Garden Bridge. The former had poor 3 lines of defence, no internal audit and weak procurement skills, the latter was a Boris Johnson vanity project with no proper governance due to Johnson’s pressure and interference.
Roy discussed the principles of assurance reviews from APM’s Guide to Integrated Assurance (Free to Members), which include: independence, accountability, risk based, and impact, etc
Human factors are important in project reviews. The skills and knowledge of the review team, building trust with the project team to avoid defensiveness, body language, and team dynamics, which can only be assessed face to face, active listening, flexibility and objectively.
Click here for further content: https://www.apm.org.uk/news/a-beginner-s-guide-to-project-reviews-everything-you-wanted-to-know-but-were-too-afraid-to-ask/
Dr. Nasir Mustafa CERTIFICATE OF APPRECIATION "NEUROANATOMY"Dr. Nasir Mustafa
CERTIFICATE OF APPRECIATION
"NEUROANATOMY"
DURING THE JOINT ONLINE LECTURE SERIES HELD BY
KUTAISI UNIVERSITY (GEORGIA) AND ISTANBUL GELISIM UNIVERSITY (TURKEY)
FROM JUNE 10TH TO JUNE 14TH, 2024
How to Manage Access Rights & User Types in Odoo 17Celine George
In Odoo, who have access to the database they are called users. There are different types of users in odoo and they have different accesses into the database. Access rights are permissions that can be set for the individual or group of users. This slide will show How to Manage Access Rights & User Types in Odoo 17.
How to Manage Shipping Connectors & Shipping Methods in Odoo 17Celine George
Odoo 17 ERP system enables management and storage of various delivery methods for different customers. Timely, undamaged delivery at fair shipping rates leaves a positive impression on clients.
2. APPLICATIONS OF
ARTIFICIAL INTELLIGENCE
With the fast-paced advancements in the field of Artificial Intelligence and
related technologies, one can witness AI applications being used in their
routine lives. Automated customer support systems, chatbots, and
personalized shopping experience with product recommendations are a
common example of this.
With smart autonomous cars driving on roads and autonomous drones
delivering items directly to doorsteps, a great deal of transportation and
service issues will be resolved effectively. Companies like Walmart and
Amazon are investing heavily in making the drone delivery a reality and an
efficient system of delivering goods faster and safely.
The creative fields are also adopting AI as a means of exploring new ideas in
art and music in this technologically advanced era. Other applications of AI
can be witnessed in the new-age Security and Surveillance systems where
technologies like image processing, data science, facial recognition, and
voice recognition are helping security forces to develop better systems to
identify and act upon security breaches, many a time before they actually
happen.
1
INTRODUCTION
Data has garnered a great deal of attention over the past decade and is
being considered as the new oil because it’s extremely valuable to
organisational success. This data economy with its vast reservoir of vital
information is pushing for innovations in data science, Artificial Intelligence,
Machine Learning, and Deep Learning technologies. Machines are learning
from data to derive patterns and insights to aid various applications and
processes.
3. 22
IMPORTANCE OF AI
Artificial Intelligence is influencing people and businesses at a massive scale
and has become an inseparable component. The scope of AI will only
increase in the near future. The everyday interaction with AI to make our lives
simpler is evident in the way we use our smartphones to navigate around the
city with live insights on traffic, suitable and fastest routes, and other
recommendations. Also, the virtual digital assistants such as Cortana or
Alexa are making our lives simpler than ever.
Businesses are exploring the scope and utility of AI to devise new products,
processes, and capabilities with an aim to gain competitive advantage along
with saving cost and time. The vast amount of data collected by businesses
along with concepts like the Internet of Things are driving marketing
decisions and improving operations and customer service.
4. INDUSTRY APPLICATIONS
OF AI
Healthcare and Entertainment are two sectors that are being massively
influenced by Artificial Intelligence.
Healthcare
AI technologies are being developed to help medical institutions to
streamline clinical as well as administrative healthcare processes. Accenture
analyzed the AI applications in healthcare in terms of estimated potential
annual benefits by application by 2026. Here is what the study established:
3
Source: Forbes Insights - AI And Healthcare: A Giant Opportunity
ROBOT-ASSISTED SURGERY
$40B
VIRTUAL NURSING ASSISTANTS
$20B
ADMINISTRATIVE WORKFLOW ASSISTANTS
$18B
FRAUD DETECTION
$17B
DOSAGE ERROR DETECTION
$16B
CONNECTED MACHINES
$14B
CLINICAL TRIAL PARTICIPANT IDENTIFIER
$13B
PRELIMINARY DIAGNOSIS
$5B
AUTOMATED IMAGE DIAGNOSIS
$3B
CYBERSECURITY
$2B
5. Entertainment
Today media and entertainment companies are
training ML algorithms to design advertisements and
develop film trailers. Personalized user experience is
given a lot of importance with streaming channels that
recommend content based on specific user activity
and behaviour.
Artificial Intelligence softwares are improving the
speed and efficiency of the media production process
and the ability to organize visual assets. Many gaming
platforms are also adopting new technologies to bring
more interactive gaming experience. Sports show
maximum affinity towards using Artificial Intelligence
for game preparation and real-time analysis of the
on-field action.
Banking and Finance
Applications of Artificial Intelligence in Banking and
Finance are set to revolutionize the industry and bring
it up to a more secure and sophisticated platform. AI is
being used to detect anti-money laundering patterns,
which is much more efficient than the traditional
rule-based software systems.
Talking about Algorithmic trading, reports suggest that
automated AI systems are behind more than 70% of
the trading today. One of the fields where AI has
proved to provide the most accurate and superior
results is ‘Fraud Detection’. Apart from the regulatory
and legal aspects, banks and financial institutions are
using chatbots and virtual assistants to provide better
customer service than ever.
4
6. Marketing
AI-generated content is big news among the
content-generating and aggregating agencies and
professionals. Smart content curation allows better
engagement with visitors on a website by showing
content pieces relevant to them. Another aspect is
Voice Search which is set to change the future SEO
strategies. Brands need to keep up and leverage huge
returns on organic traffic with high purchase intent.
Marketing automation, programmatic media buying,
propensity modelling, predictive analytics, and lead
scoring are other applications where AI can leverage
better results. Some Machine Learning algorithms can
run through a vast amount of historical data to draw
insights on the ads which performed best, audience
targeted for the same, and buying stage.
AI is also helping in evolving the concept of dynamic
pricing, web and app personalization, chatbots, and
re-targeting, some of the marketing aspects directed
towards conversion.
Retail and e-commerce
Image search is a very important application of
Artificial Intelligence for e-commerce. It makes it so
much easier for shoppers to search products similar to
a product image across sellers online. AI is also
deriving sense and insights out of the massive amount
of data generated by the minute.
Product recommendations, Chatbots, and efficient
after-sales services backed by AI are directed towards
high customer satisfaction, engagement, and finally,
loyalty. AI is also helping retail brands manage their
inventories, improve their CRM, and develop a better
sales process.
5
7. Manufacturing
Smart factories are primarily driven by AI concepts and
technologies taking active measures for increased
productivity, environment friendliness, and quality of
life at these intensive workplaces. Artificial Intelligence
is being applied for quality checks, maintenance, and
creating more reliable designs and layouts for the
plant and its processes.
Apart from that, it is also reducing environmental
impact by applying methods of cutting down waste
and using the resources optimally. An example of this
is demonstrated by Siemens, where hundreds of
sensors feed an AI operating data processing system
to adjust fuel valves to keep emissions as low as
possible.
Applications of AI are myriad in manufacturing and not
just limited to the ones mentioned here. One can
witness how AI works wonders with different aspects of
the supply chain.
6
The outcome of these applications and the general acceptability of these
technologies can be seen in the form of increased job opportunities and new
work domains. This has created a necessity to learn new skills and move from
the older redundant roles to the new high paying jobs, given one acquires
the required skillset and subject matter knowledge.
There are opportunities to upskill and move horizontally and vertically into
the organizations across industries making a career which is highly rewarding
and relevant to this age and time. With sophisticated skills and continuous
learning, employees can deem themselves irreplaceable and make a strong
position for themselves in the job market as a highly preferred resource.
The myth that AI will eat up jobs is being constantly proven wrong by these
innovative solutions and applications of Artificial Intelligence. The jobs will
surely be displaced by leaving some roles redundant, but a lot more
opportunities will open up demanding an upskilled workforce.
8. 7
CAREER OPPORTUNITIES
It would not be wrong to state that
Artificial Intelligence has picked up
the pace to reach its prime, and is
going to see an upward graph
over the coming years. The career
opportunities likewise are growing.
The challenge is that the supply of
skilled resources in Artificial
Intelligence lags behind the demand
substantially. These are the jobs that
have been vacant for a stretch of 12
months straight. This gap showcases
a huge opportunity and promising
career prospects for mid and
senior-level professionals across
industries.
57%
of the companies in India
hiring for AI roles.
4000
AI jobs were vacant in the
year 2018
You can enter into the field of Artificial Intelligence and pursue a career in the
same by following these five steps:
■ Understand the AI career landscape
■ Research and list out popular job roles in the field of AI and evaluate which
suits you best
■ Understand the education and knowledge pre-requisites to pursue your
chosen job role
■ Enrol to top online or offline resources and institutions to learn from
■ Start with the job hunt to land your dream job
Source: Economic Times - 2018
9. 8
AI SALARY TREND IN INDIA
A career in Artificial Intelligence pays off really well.
` 14.3lacs per annum
The median salary of AI professionals in India
City-wise remuneration trends
MUMBAI
15.6L
14.5L
10.5L
BENGALURU
CHENNAI
Average Salary per annum (INR)
40%
Entry level
professionals
60-80%
Salary
hike
20-30%
Salary
hike
Job switch in
AI
domain
Job switch in
Other
domains
4%
Senior level
professionals
> 6L p.a.
Salary
> 50L p.a.
Salary
Source: Economic Times - 2018
Source: Economic Times - 2018
10. 19
AI JOB TITLES
MIT Sloan’s research aggregated the responses of over 3000 analysts,
executives, and managers across industries and deduced that 85% of them
believed that AI will provide a competitive advantage to their businesses.
But, on the other hand, only 20% have started to implement this technology
in their own businesses. Also, the world economic forum’s report forecast
that AI and robots at the workplace will create 58 million net new jobs in the
coming years. The landscape is wide and varied for a career in AI and
professionals can expect a major shift in the quality, number, location, and
permanency in AI specialist roles.
01
Software
Engineer
02
Data
scientist
03
AI
researcher
04
Intelligence
specialist
05
Consultant
06
AI data
analyst
07
Machine learning
engineer
08
Sales
engineer
09
Product
manager
10
R&D Engineer
The job roles offered by companies hiring for AI roles
11. 110
AI HIRING INDUSTRIES
IT
tops the race among industries that are
massively hiring for these AI roles.
2.5L
new jobs in 2019 in India by IT
industry.
Source:“IT hiring projections for 2019” by
TeamLease
Other industries that are most likely to adopt AI and Machine Learning
solutions and hence create job opportunities for experts are:
MANUFACTURING &
SUPPLY CHAIN
HEALTHCARE
CONSUMER
& RETAIL
AGRICULTURE
FINANCIAL
SERVICES
EDUCATION
PUBLIC & UTILITY
SERVICES
TELECOM
The top 10 organizations which offered most numbers of job opportunities in
the year 2018 were:
(Source: Economic Times - 2018)
12. 11
SAMPLE
JOB DESCRIPTIONS
ARTIFICIAL INTELLIGENCE ENGINEER
Responsibilities
■ Set up and manage AI development and production infrastructure
■ Help AI product managers and business stakeholders understand the
potential and limitations of AI when planning new products
■ Build data ingest and data transformation infrastructure
■ Identify transfer learning opportunities and new training datasets
■ Build AI models from scratch and help product managers and stakeholders
understand results
■ Deploy AI models into production
■ Create APIs and help business customers put results of your AI models
into operations
Skills Required
■ Demonstrated proficiency in multiple programming languages with a
strong foundation in a statistical platform such as
Python, R, SAS, or MatLab
■ Experience building AI models in platforms such as
Keras, TensorFlow, or Theano
■ Demonstrated commitment to learning about AI through your own
initiatives through
courses, books, or side projects
13. 12
MACHINE LEARNING ENGINEER
Machine Learning Engineer responsibilities include creating machine learning
models and retraining systems. To do this job successfully, you need
exceptional skills in statistics and programming. The knowledge of data
science and software engineering is an added advantage. Your ultimate goal
will be to shape and build efficient self-learning applications.
Responsibilities
■ Study and transform data science prototypes
■ Design machine learning systems
■ Research and implement appropriate ML algorithms and tools
■ Develop machine learning applications according to requirements
■ Select appropriate datasets and data representation methods
■ Run machine learning tests and experiments
■ Perform statistical analysis and fine-tuning using test results
■ Train and retrain systems when necessary
■ Extend existing ML libraries and frameworks
■ Keep abreast of developments in the field
Skills Required
■ Proven experience as a Machine Learning Engineer or similar role
■ Understanding of
data structures, data modelling & software architecture
■ Deep knowledge of
mathematics, probability, statistics & algorithms
■ Ability to write robust code in
Python, Java and R
■ Familiarity with machine learning frameworks like Keras or PyTorch
and libraries like scikit-learn
■ Outstanding analytical and problem-solving skills
14. SKILLS REQUIREMENT
The top skills that employers seek in AI professionals are Natural Language
Processing, Machine Learning, Neural Networks, Cloud Computing, Data
Science, Analytics, and Pattern Recognition among others.
While the technical skills on your resume will surely land a good job in
Artificial Intelligence, you cannot ignore the supporting written and verbal
communication skills that are needed to convey how the AI tools and
services are deployed within the business or industrial processes.
Professionals are required to be hands-on with the following tools,
techniques, and programming languages:
13
Python
Object-Oriented Programming, Python is a
very useful and robust programming
language that focuses on RAD (Rapid
Application Development). The
ever-changing libraries are the reason that
it is an ideal choice for developers working
on AI projects.
The benefits of using Python are:
PREBUILT
LIBRARIES
MINIMAL
CODING
PLATFORM
AGNOSTIC
FLEXIBILITY
15. 14
Java
This programming language derives a
major part of its syntax from C and C++. It
is fast, powerful, and secure along with
easier debugging. Java is
architecture-neutral and hence portable
with no implementation-dependent
aspects of a specification. The
multi-threading feature makes it possible
for a program to perform various tasks
simultaneously.
The benefits of using Java are:
SCALABILITY BETTER USER
INTERACTION
PLATFORM
AGNOSTIC
LARGE-SCALE
PROJECTS
R
Considered as a Statistical Software, R is
specialized for statistics, data visualization,
and data analytics with graphical tools. It
has effective data handling and storage
facility and runs on all platforms, being
easily ported to another platform. A
common application is in monitoring user
experience in Social Media.
The benefits of using Python are:
Other tools and techniques which are also important are Hadoop, Data
Mining, Spark, and SAS.
OPEN SOURCE
& FREE
CAN CONNECT WITH
OTHER LANGUAGES
ADVANCED
VISUALIZATIONS
16. SUCCESS STORIES
15
The peer learning aspect is something that you
guys should definitely be proud of. I should say
that I have been able to connect with wonderful
people, both technically and personally, after
enrolling in the course. I am always an advocate
for the quote - when you teach you learn more
about what you teach. Here my peers are both
teachers and students enriching each other's
technical expertise to a vast extent.
SAI
VENKATESHWARAN
SRINIVASAN
Senior technical lead
The course provides a good balance of
theory and practical application of different
techniques covered through sessions taken
by renowned faculty. It balances regular and
online coursework amidst work schedules
and enhanced by opportunities to engage
with leading faculty and outstanding peers. LAKSHMINARASIMHAN
SANTHANAM
Director - Data Analytics
and Automation
The Capstone project gave me an opportunity
to optimize and automate the best practices
used in the industry.
MONDAL SUDIPTA
Senior Data Analyst
17. ABOUT THE PROGRAM
The PGP-AIML (Post Graduate Program in Artificial Intelligence and Machine
Learning) is designed with the needs of the modern workforce in mind. It is a
comprehensive program that covers everything that a professional would
need to launch their career in AI.
We do this by offering:
■ Real-world examples and projects that help you apply the skills you’ve
learned
■ Personalised mentorship to clear your doubts and offer guidance in your
learning journey
■ Interacting with experienced industry practitioners to offer context
Our mentors are highly experienced professionals, working in the leading
companies of the world. They will help you with career guidance, clearing
your doubts about the course content, and offering industry context that
helps you materialize and transform what you’ve learned into industry-ready
skills.
Also, when you enrol in the PGP-AIML, you will solve real-world industry
problems by utilizing cutting-edge tools such as TensorFlow, Python Keras,
and libraries that include matplotlib, Pandas, Numpy, NLTK, Sci-kit learn and
much more.
16
Other AI courses
PGP-ML
(PG program in
Machine Learning)
AIFL
(Artificial Intelligence
for Leaders)
DLCP
(Deep Learning
Certification Program)
PGP-ML
(PG program in
Machine Learning)
18. 17
ABOUT GREAT LEARNING
Great Learning is an ed-tech company that offers programs in career critical
competencies such as Analytics, Data Science, Big Data, Machine Learning,
Artificial Intelligence, Cloud Computing, DevOps, Full Stack Development
and more.
Our programs are taken by thousands of professionals globally who build
competencies in these emerging areas to secure and grow their careers. At
Great Learning, our focus is on creating industry-relevant programs and
crafting learning experiences that help candidates learn, apply and
demonstrate capabilities in areas that are driving the future.
6
Million+hours of learning
to professionals worldwide
with thousands of them being able to achieve a successful career progression
in leading companies such as
Microsoft, Amazon, Adobe, American Express, Deloitte,
IBM, Accenture, McKinsey
and more.
We are on a mission to make professionals proficient and future-ready. In the
last 5 years, we have been able to deliver