By | Sanjay
The differences and similarities between AI, ML and DS can range from conceptual, and foundational to abilities and skills. We will discuss how all these domains are inter-related to each other and what comparisons we can draw between them in terms of job scope, salaries, subjects, concepts, etc.
B.Tech CSE Artificial Intelligence and Data Science gives maximum emphasis on inter-relations between AI and DS and focuses on big data analytics, fuzzy technologies and artificial neural networks.
Relations between Data science, artificial intelligence, and machine learning
The goal of artificial intelligence and data science is to replicate human intellect through machines through a variety of applications, platforms, and other tools. Artificial intelligence is the planned action-reaction to perception. Best Colleges for B.Tech in Artificial Intelligence also emphasizes on teaching students how to approach new challenges in these areas.
Observation > Planning > Action > Observational Feedback
Different components of this pattern or loop are used by data science to address particular issues. For instance, data scientists attempt to find patterns using the data in the first step, Perception. Similar to the previous step, planning involves two elements:
- Finding all logical solutions
- Identifying the best solutions out of all solutions
Data science develops a framework that connects the aforementioned ideas and aids in business advancement.
The best way to understand machine learning is in the context of its environment, or the system it’s utilized inside, even though it can be explained by treating it as an independent subject.
Simply described, machine learning is the interface between data science and artificial intelligence. This is because it involves gradually learning from data. AI is the tool that data science uses to obtain outcomes and answers to certain issues. But its machine learning that makes it possible to accomplish that. The Search Engine on Google is an actual instance of this.
Data science specifically involves machine learning and AI. Deep Learning is a sub-technology that is covered by machine learning itself. B.Tech CSE in Artificial Intelligence and Data Science.
A type of machine learning is deep learning. However, it differs in the usage of neural networks, where we partially mimic brain function and employ a 3D hierarchy to find patterns in data that are far more valuable.
Difference between Artificial Intelligence and Machine Learning
|Artificial Intelligence||Machine Learning|
|The goal of AI is to create intelligent computer systems that can tackle challenging issues like humans.||ML enables machines to gain knowledge from data in order to produce accurate results.|
|Weak AI, General AI, and Strong AI are three categories for AI that differ in capacity.||ML can be divided into three categories: reinforcement learning, unsupervised learning, and supervised learning.|
|The goal of AI systems is to increase the likelihood of success.||Accuracy and patterns are the main challenges with machine learning.|
|A machine may imitate human behavior thanks to AI.||AI includes machine learning as a subset.|
|Focuses on organized, semi-structured, and unstructured data primarily||Focuses on data that is structured and semi-structured.|
|Virtual assistants like Siri, chatbots, intelligent humanoid robots, and other technologies are some applications of AI.||Applications of ML include Facebook auto friend tagging systems, search algorithms, and more.|
Difference between Data Science and Machine Learning
|Data Science||Machine Learning|
|Data science aids in generating insights from data that address the complexities of the real world.||By recognizing patterns in previous data, machine learning aids in properly predicting or classifying outcomes for new data points.|
– domain expertise
– strong SQL
– ETL and data profiling
– NoSQL systems, Standard reporting, Visualization
– Python/ R Programming
– Strong Mathematics Knowledge
– Data Wrangling
– SQL Model-specific Visualization
|Massive data is typically handled by systems that are horizontally scalable.||For demanding vector processing, GPUs are preferred.|
|A set of tools for working with unstructured raw data||The mathematical principles and algorithms that underlie them have a significant amount of complexity.|
|Most of the input data can be used by humans.||Data input is altered specifically for the kind of algorithms being used.|
The Difference among Machine Learning, Artificial Intelligence, and Data Science
Although there may be connections and relationships among the phrases “data science,” “machine learning,” and “artificial intelligence,” each is distinct and has a specific function. Machine learning is a subset of data science, which is an all-encompassing word. The key distinction between the two terminologies is as follows.
|Artificial Intelligence||Machine Learning||Data Science|
|Comprising machine learning.||Artificial intelligence’s subset.||Contains a variety of data operations.|
|Computers can learn automatically with the aid of artificial intelligence, which combines massive volumes of data through repetitive processing and clever algorithms.||Machine learning employs effective software capable of utilizing data without being specifically instructed to do so.||For analytical reasons, data is collected, cleaned, and processed using data science techniques.|
|The following are some of the more well-known AI tools: 1. Tensor Flow 2. Scikit Learn
|The most common tools used by machine learning are: 1. Amazon Lex2. IBM Watson Studio.
3. Azure ML Studio by Microsoft
|The following are some of the more well-known data science tools: 1. SAS 2. Tableau 3. Apache Spark
|The most well-known AI applications are chatbots and voice assistants.||Facial Recognition and recommendation systems like Spotify are two common examples.||Popular applications of data science include healthcare analysis and fraud detection.|
Artificial Intelligence and Machine Learning Jobs and Salary
A Programming enthusiast who aids in the understanding and knowledge acquisition of machines is known as a machine learning engineer. A machine learning engineer’s primary responsibility is to write programs that allow a computer to perform certain tasks without explicit programming. Their main duties include gathering data sets for analysis, customizing digital experiences, and determining company needs. The pay for a Machine Learning Engineer and a Data Scientist can vary depending on their qualifications, work history, and employer.
Colleges for B. Tech Artificial Intelligence and Machine Learning offer campus placements with lucrative salary packages in big MNCs and corporates. Here are some of the popular jobs for graduates in B. Tech CSE with AI and ML.
Machine Learning Engineer Salary
- Machine Learning engineer – INR 6,51,000 PA
- AI data analyst – INR 8,26,000 PA
- Robotics Expert – INR 15,40,000 PA
Artificial Intelligence and Data Science Jobs and Salary
Data scientists are experts who find, collect, and examine huge data collections. A Data Scientist is essential in today’s environment because the majority of business decisions made today are based on insights obtained through data analysis. They concentrate on processing and modeling organized and unstructured data as well as interpreting the results to provide plans that stakeholders can actually follow.
Best Colleges for B. Tech in Artificial Intelligence and Data Science offer campus placements with lucrative salary packages in big MNCs and corporates. Here are some of the popular jobs for graduates in B. Tech CSE Artificial Intelligence and Data Science.
Jobs in B. Tech CSE Artificial Intelligence and Data Science
- Data Scientist – INR 5-15 LPA
- Database Developer – INR 3-12 LPA
- Big Data Engineer/Architect – INR 4-14 LPA
- Data Analyst – INR 3-10 LPA
- Tech CSE with Internet of Things IoT
An engineering specialization known as B. Tech in IoT, or the “Internet of Things,” focuses on the network of diverse things that are outfitted with sensors, software, and other technologies to connect and exchange data with other systems and devices over the Internet. Participants learn how to maintain online connections and how to use the Internet of Things in their daily lives in this course.
- Internet of Things
- Cloud Computing
- Software Development
- Statistical Data Analysis
Students who complete a B. Tech in IoT program may work in this field as IoT Engineers, IoT Experts, Development Engineers in IoT Applications, and in other positions. This article offers a glimpse into what is covered in the subject and all of its components so that the student will have a better understanding of the course.
These are the following career options in B. Tech in IoT:
- Data analysts – INR 3-10 LPA
- Network engineer – INR 2-5 LPA
- Protection engineer – INR 3-15 LPA
- Device and Hardware engineer – INR 4-14 LPA
- Cell and UI development – INR 2-10 LPA
Fees and Admission
Take a quick glance at the different fee structures of B.Tech programs in AI, ML, DS, and IoT specializations along with the admission process.
|Specialization||Fees per annum||Admission|
|B. Tech CSE with AI and ML||INR 1-1.5 LPA||Both entrance-based and merit-based admissions|
|B. Tech CSE with AI and Data Science||INR 1-2 LPA||Both entrance-based and merit-based admissions|
|B. Tech CSE with IoT||INR 1-1.5 LPA||Both entrance-based and merit-based admissions|
Despite the overlap between data science, machine learning, and artificial intelligence, each field has its own application fields and unique features. Data science specialists now have more chances thanks to the data science market’s expansion of numerous service and product sectors. The Best colleges for B.Tech in Artificial Intelligence offer specializations in all three domains and students can choose from any of them depending on their future goals and career obligations.
Q1. WHAT IS BETTER, AI & ML OR AI & DS?
Depends on your career choices. If you want a career in data expertise, AI and DS are best for you. But if you want to seek a career in robotics, then you should go for B. Tech CSE with AI and ML.
Q2. WHAT IS THE REQUIREMENT FOR ADMISSION IN B. TECH CSE WITH AI AND ML?
All applicants must clear 10+2 from the science stream with mathematics and at least 55% minimum score in aggregate.
Q3. WHICH ENTRANCE EXAM IS BEST FOR B. TECH CSE IN ARTIFICIAL INTELLIGENCE AND DATA SCIENCE?
JEE Main and JEE Advance are the best national-level engineering entrance exams. It is acceptable by every university, college, and institution in India.
Q4. WHY B. TECH CSE IN ARTIFICIAL INTELLIGENCE IS BEST FOR ENGINEERS?
Because AI is one of the most popular B. Tech specializations with a wide range of job opportunities and a lucrative salary package.