What is the Future of Data Science & AI?
Congratulations Engineers! Welcome the newest addition to the GATE 2024 subjects. We are all aware of the fact that technology is modernizing, and there is no stop to it. From using the PC to gradually using laptops and MACs, using wired phones and earphones to using wireless gadgets for more convenience. No doubt, technology is built for our convenience. With increasing dependency on technology, businesses are also functioning effectively.
IISC Bangalore, looking at the future of data science and the gradual growth of the internet, has introduced Data Science and Artificial Intelligence (DA) to the GATE 2024 Exam. The candidate opting for the subject does have a bright future ahead, as data is the king nowadays.
As you gradually read this blog, you’ll get all the possible insights and the future of data science and artificial intelligence.
Data Science
Data Science is a study where a huge amount of data is used with various contemporary tools and techniques to extract hidden patterns, obtain valuable information, and make business decisions. In order to generate predictive models, data scientists use advanced machine learning algorithms.
Data obtained through analytical methods can be displayed in different ways and can be from diverse origins.
Data Science enhances business understanding by applying mathematical techniques with business expertise. By this method, businesses can create predictive models with a statistical analysis.
However, data science is required in sectors like education, finance, marketing, healthcare, transport, manufacturing, weather forecasting, predicting disease outbreaks, fraud detection, etc.
Let’s look how the raw data transforms into playing a pivotal role:
- Acquisition- Data collection happens during the acquisition stage. The information gathered in this case is unstructured and raw.
- Exploration- The most time-consuming task in life is this. Here, the information is sorted and classified as either useful or useless. The data scientist then presents it in a state that is prepared for the following action.
- Modeling- A data scientist evaluates the data at this stage of the process to decide which model will work best for the required analysis.
- Analysis- The core of the entire procedure is this. The data is subjected to a number of analyses to produce the desired outcomes.
- Reporting- The results are presented in an understandable format, such as a chart, diagram, or straightforward report.
Future of Data Science
Today, with advanced technology and widespread internet access, the field of Data Science has a promising future. Skilled and professional data scientists are in high demand as data heavily influences our world. Businesses and industries rely on these experts to make sense of the vast amounts of information available, guiding them toward informed decisions.
As more and more data floods the internet, the role of Data Science becomes increasingly crucial. Whether it’s preventing fraud in banks or measuring a nation’s happiness, Data Science is here to stay. This means there will be plenty of jobs in this field in the future. The industries that are sure to benefit the most are:
- Healthcare advancements- The healthcare system will quickly identify any deficiencies with a larger patient database, which can assist the government in immediately mitigating forthcoming health crises.
- Weather forecasting- With enough data from prior years and strong analysis tools, predicting the approaching storms could soon be possible. It can save hundreds of lives and reduce property losses.
- Fraud Detection- Fraudulent transactions are immediately corrected if algorithms and AI tools are in place. If that is the issue considered by an AI, such activities can also be stopped.
- Logistics- AI systems have already advanced, with Google Maps telling us which route to take or avoid due to traffic. This system can be strengthened, and various issues like traffic accidents can be resolved as well.
- Recommendation systems- With the help of websites and apps like Netflix, Amazon Prime, Disney, and other OTT platforms, the entertainment industry has already benefited from all the data collection that has been done. Your watch history is a rich source of information for these businesses. So, as you watch more content on a platform, your suggestions will become more accurate.
Artificial Intelligence
Artificial intelligence is when machines, particularly computer systems, simulate human intelligence processes. Examples of AI applications are expert systems, NLP (Natural language processing), speech recognition, and machine vision.
How Artificial Intelligence Works
AI enables software to automatically learn from patterns or features in the data with the help of intelligent algorithms, quick, iterative processing, and large amounts of data. Artificial intelligence (AI) is a big field with different parts, like theories, methods, and technologies. These parts are called key subfields, and they all come together to form AI.
- The construction of analytical models is automated by machine learning. To uncover hidden patterns in data without being explicitly programmed on where to look or what to conclude, it employs techniques from physics, operations research, statistics, neural networks, and statistics.
- A neural network is a type of artificial intelligence that consists of interconnected units that communicate with one another and process information by responding to outside inputs. Finding connections and deriving meaning from undefined data requires several iterations of the data.
- In order to learn complex patterns from massive amounts of data, deep learning makes use of enormous neural networks with numerous layers of processing units. It does this by utilizing improved training methods and computing power advancements. Image and speech recognition are two common applications.
- To identify what’s in a picture or video, computer vision uses deep learning and pattern recognition. Machines that can process, analyze, and comprehend images will be able to capture real-time images and videos and comprehend their surroundings.
- Natural language processing (NLP) refers to computers’ ability to analyze, comprehend, and generate human language, including speech. The next level of NLP, called natural language interaction, allows users to communicate with computers to complete tasks using everyday language. The next level of NLP, called natural language interaction, allows users to communicate with computers to complete tasks using everyday language.
Importance of Artificial Intelligence
AI has the ability to change our way of working, playing, and living. In several industries, AI is far more efficient than humans at completing jobs. Particularly when it comes to repetitive, detail-oriented jobs like reviewing a large number of legal documents to make sure the relevant spaces are filled in correctly, AI systems typically complete tasks swiftly and with relatively few errors.
- Customer Service work: It is very expensive and difficult for businesses that deal with customers to properly handle customers and their inquiries. Chatbots and other AI tools enable users to emphasize their questions and receive a prompt, AI-generated response. Businesses can avoid building large, costly customer service installations in this way.
- Fraud Detection: AI is very important when it comes to detection of fraud. Fraud management systems with AI capabilities are able to recognize and stop a variety of frauds, including identity theft, phishing scams, and payment fraud.
- Quality Control: AI helps to enhance quality in industries such as manufacturing goods, healthcare, and food processing.
Future of Artificial Intelligence
Artificial intelligence is actually influencing practically every aspect of the economy. Generative AI has become more well-known due to tools like ChatGPT and AI art generators, it is already the driving force behind the development of sectors like big data, robotics, and the IoT.
Here are a few parameters from the three sectors concerning AI:-
| BIG DATA | ROBOTICS | IoT |
|---|---|---|
| A huge amount of data sets that cannot be stored, processed, or evaluated using conventional tools is called big data. | Robots learn and perform specified tasks using machine learning algorithms by monitoring and mimicking human behavior. AI, through machine learning, provides robots with computer vision, allowing them to navigate, detect, and react appropriately. | The “Internet of Things” (IoT) is a network of real, physical items, or “things,” that have been implanted with sensors, software, and other technologies to enable online data sharing and communication with other systems and devices. |
| Certainly, there are numerous applications where big data is utilized with AI like healthcare and medical research, financial services, e-commerce, retail, social media, manufacturing and supply chain management, etc. | Autonomous vehicles like self-driving and drones are prime examples of robotics with AI. | Smart homes including smart thermostats, light and security cameras, wearable sensors, and healthcare monitors collect real-time health data. |
Artificial Intelligence Contribution
Below is a list of the many markets that have embraced artificial intelligence and how it is enhancing their work:
AI in education
Teachers will have more time to do other tasks because of AI’s ability to grade assignments automatically. Students are able to learn at their own convenient pace because it can assess their performance and adapt to their rate of learning. Aside from providing additional support, AI tutors can ensure that students stay on the right track academically.
For example: Automated Grading System- Optical marking recognition OMR criteria for the evaluation of the objective type of questions is the most popular automated grading system.
Administrative Task- AI helps in reducing administrative tasks like rescheduling curriculum, rescheduling classes, making attendance, grading, etc.
AI in healthcare
Big efforts are focused on helping patients get better and saving money. The medical sector is using machine learning to diagnose medical conditions more accurately and quickly than people can.
AI in business
In order to find out how to better serve clients, machine learning algorithms are being included in analytics and customer relationship management (CRM) platforms.
AI in entertainment and media
Targeted advertising, content recommendations, distribution, fraud detection, script creation, and movie production are all areas where the entertainment industry makes use of AI.
Examples of ARTIFICIAL INTELLIGENCE
Since ChatGPT was recently released you may have heard a lot about artificial intelligence. Even if you have not used ChatGPT, you still must have engaged with artificial intelligence at least once every few minutes.
- Maps and Navigation
- Chatbots
- Face Recognition and Facial Detection
- Digital Assistants
In the upcoming GATE 2024 examination, IISc (Indian Institute of Science) Banglore is taking the initiative to meet the growing demand and promising future prospects in the field of Data Science & AI. As a response to this exciting development, MADE EASY has introduced a specialized course focused on Data Science and Artificial Intelligence (DA) to enhance GATE preparation for those aiming to excel in this new subject. This is the most demanding engineering field in the future so aspiring DA candidates now have the opportunity to enroll in this course and take a significant step towards achieving their goals of success.
MADE EASY Online Course for Data Science and AI (DA)
FAQ
1. What is DATA SCIENCE?
Data Science is the collection, processing, and analysis of data to derive insights for a variety of reasons.
2. Is Data Science a good career for the future?
Yes. Data Science is a good career for the future. Due to the high demand for data with advanced technology and widespread internet access, data scientists have a good career ahead of them. Aspirants who love to work with data and are curious about solving problems can find themselves in an interesting and fun career as data scientists.
3. Can a Data Analyst become a Data Scientist?
Yes, Data analysts can advance themselves to become Data Scientists by advancing their level of mastering programming, acquiring strong mathematical and analytical skills, and comprehending machine learning methods.
4. What is Artificial Intelligence?
Artificial intelligence (AI) means teaching machines to think and learn like humans. It helps computers do smart things, like understand languages and make decisions. AI is used in many areas to make tasks easier and more efficient.
5. How is AI a part of our day-to-day activities?
AI has been there in our day-to-day activities like chatting, designing, writing, video making, facial recognition, smart speakers, and many more. In fields like digital marketing and CRM, people often use AI to make their work easier and more efficient.
6. How does AI contribute to the future?
AI is contributing through automation. Machine learning is helping the computer perform tasks that a human could only complete.
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