which is the best and easy course ?? cse or cse sub groups like cse-AI or cse-DATASCIENCE or cse -DEEP LEARNING or cse -ROBOTICS
Doing B.Tech with CSE is very good career in these days. Various technologies are used every day. The modern era is the era, where technology is used in every field.
Now, AI and ML are used very much today. Machine Learning is the technology where researchers are doing their best to do something new. Researchers like Andrew Ng, which are specialist of ML are themselves involved in making the machine to do work like humans. ML is used in Facebook, Instagram, Netflix and many more. AI also known as artificial intelligence is the most excited field of computer science. It is also very interesting as ML as every engineer dreams to create an AI like Jarvis.
Doing CSE with your interest is important. If you took cse with specialisation, you will become bounded to that field. Also, when you apply for jobs in various companies you are only selected for work of your field. On the other hand, if you take cse without specialisation, you will do coding very much which is very useful for you. Today every company first conducts a round of coding to select candidates. Also, coding is used everywhere in AI and ML and data science, coding is very essential. If you know coding you can get job in any field,
ML and AI are complementary, but they target different goals.
AI has a very specific purpose of building an intelligent agent that can take rational decisions under various different circumstances. By its very nature, the intelligent agent needs to interact with environment that were built for humans and hence must be capable of human-like capabilities i.e reading natural language text, understanding speech, recognizing different objects etc. The application focus is something like, a robot capable of automatically identifying and fixing issues that can occur in a nuclear reactor or a robot capable of self navigation, experimentation and reporting "interesting" observations during extra planetary missions etc. From these application, we also get some higher order AI problems. For example, a robot self-navigating a planet, needs to plan and chart its course from point A to point B or a robot that is attempting to fix a leak in a nuclear reactor needs to identify the set of task to perform so that the leak is fixed.
The goal of ML is to assimilate known knowledge in an abstract form called models, and be able to predict certain unknowns for instances that will be seen in the future. For example, in an email spam classification task, the goal is to learn a model from a known set of emails that have been labeled as spam or not spam and be able to predict whether the new email that we just received is spam or not spam. Classification is just one concrete instantiation of ML goal. Clustering can be thought of as predicting cluster variables for future instances and Regression can be thought of as predicting function values for points that haven't been observed so far etc.
AI with its very specific application focus can use tools built in ML to achieve its goals. However, ML serves a much broader class of problems.
With these in mind, what you want to start from is entirely upto you. For example, if you want to build planet-navigating robots then you probably need to start from AI, learn about the various interesting problems involved in AI, see what kind of ML tools you will need to learn, come to ML learn those tools and go back to AI. However, if your interest lies in building the ML tools that serve a fairly broad class of problems many of which are relevant in the real world today [1], then you may want to start learning ML first.
Note that, both ML and AI are vast fields with many things to learn. Even though I suggest switching from ML to AI and AI to ML, it is not as easy as it might sound :-). Unless you know what you want to learn and how you plan to use it, you might be aimlessly going into and learning things, that may or may not be relevant to what you might want to do. Not that it is wrong, but, as humans, we have very limited time and we need to use it as efficiently as possible.
[1] From a research perspective, researching in ML can get you funds. From a job perspective, many people are hiring folks who have reasonable understanding in ML and can use various tools like weka, libSVM etc.
Best of luck
Answer laterBest online course for learning french
Hello!
These are some of the best online course for learning French-
- Rosetta Stone.
- Duolingo.
- Rocket Languages.
- Babbel.
- Mondly.
- Pimsleur.
- Memrise Languages.
- Frantastique.
- Berlitz.
- Lingoda.
Hope this information will help you.
hello sir I have one question about the language course or college if I want to try in jnu for korean language. then I also want to clear my entrance exam because I dont fill my cuet exam application. but i want to go jnu for learning my korean language, can you suggest me. what I have to do now.
DID YOU GET YOUR ANSWER, please connect with me?
I am a student of class 12th and i have physics chemistry and biology as my main subjects....not maths....can i do bca or btech in artificial intelligence and machine learning.....???
Hello,
Courses in Machine Learning or Artificial Intelligence After the 12th Grade Eligibility Criteria
-Candidates must have completed their 10+2 in science—basically, math and physics are compulsory from a recognized board.
-In the 10+2 board exam, the overall result must be at least 50%.
-The prerequisites for various artificial intelligence courses vary, however any student enrolled in class 10 is eligible to enroll in certificate programmes.
So, if you don't have math subject then you are not eligible.
Good Luck!!
my rank is 10251 general category can i get artificial intelligence and machine learning in this clg
Hello aspirant,
As cut-offs varies from year to year, it is difficult to predict exactly. For your AP EAMCET Rank, based on previous year's Closing Ranks you have chances of getting AI & ML seat in Vishnu Institute of Technology, Bhimavaram, as you have mentioned this College in your question.
Cut-offs changes from year to year and depends on many factors like category, number of students appeared in the exam, difficulty level of the exam, number of seats available, etc.
To predict Colleges based on AP EAMCET Rank, use below mentioned College Predictor Tool
https://dqxeclau.top/ap-eamcet-college-predictor
May this information was helpful.
All The Best!!
Mention some top industries that one can pursue after learning about these data processing types?
sir I got 70300 rank in ts eamcet ,i belong to ST category .do I get good college for me. in CSM (computer science engineering and artificial intelligence and mechine learning) plzz help me sir
Hello Aspirant,
With this rank it will be difficult for you to get good colleges with good branches.
Cutoff varies every year depending on various factors. Keep in mind that your chances to grab a seat will vary on the following basis:
Number of seats available
Number of students applied for the same branch
Performance of the students
The category you belong to etc.
Here are some colleges based on your rank where you can get admission :
- Abhinav Hi-Tech College of Engineering, Moinbad
- Balaji Institute of Technology & Science, Narsampet
- Bhaskar Engineering College, Yenkapally
- Sree Chaitanya College of Engineering, Karimnagar
- Ellenki College of Engineering College, Warangal
Go through this link to predict colleges based on your rank :
https://dqxeclau.top/ts-eamcet-college-predictor?utm_source=qna&utm_medium=ini-cet_cp
Use this link to get more information about cutoff :
https://engineering.careers360.com/articles/ts-eamcet-cutoff
Hope this information will help you.
Best Wishes!
I got 27570 rank in comedk...and I am interested in cse,AI, machine learning like stuff...so which college is best for me.Please be honest....
Hello Aspirant,
To get top colleges in CSE, AI&ML you need to get a very good rank. With this rank in COMEDK you can get admission in the below mentioned colleges-
- SAMBHRAM....cutoff 27105(CSE)
- MS ENGINEERING....cutoff 27234(CSE)
- CAMBRIDGE....cutoff 28283(AI&ML)
- VIVEKANANDA......cutoff 30053(CSE)
- Basaveshwar.....cutoff 30054(CSE)
- BANGALORE COLLEGE OF ENGINEERING.....cutoff 30175(CSE)
- SAHYADRI.....cutoff 31900( CSE Data science)
- ATME....cutoff 37006(CSE)
- GOPALAN....cutoff 38514(CSE)
- JAIN RESEARCH....cutoff 38899(CSE)
- GM INSTITUTE.....cutoff 39257(CSE)
- PES SHIVAMOGGA.....cutoff 40383(CSE)
- DON BOSCO....cutoff for CSE 42102 and for AI&ML cutoff 43276
You have chances to get medium colleges. You can expect average placement from this colleges. To grab good opportunities you have to prepare yourself more for off campus placements.
Cutoff keeps changing year to year. Keep in mind that your chances to grab a seat will vary on the following basis:
- number of seats available
- number of students applied for the same branch
- performance of the students
- the category you belong to etc.
Also, you can use this predictor to predict colleges based on your score:
COMEDK UGET College Predictor 2022 - Predict colleges based on your COMEDK Rank (careers360.com)
Check out previous year cutoff from the below link:
https://engineering.careers360.com/articles/comedk-uget-cutoff
Hope this information will help you .
Best wishes.
could you please tell me the difference between different courses in CSE like artificial intelligence and machine learning and also which one is better
I would suggest you to go with Artificial intelligence rather than machine learning.
AI has a very specific purpose of building an intelligent agent that can take rational decisions under various different circumstances. By its very nature, the intelligent agent needs to interact with environment that were built for humans and hence must be capable of human-like capabilities i.e reading natural language text, understanding speech, recognizing different objects etc. The application focus is something like, a robot capable of automatically identifying and fixing issues that can occur in a nuclear reactor or a robot capable of self navigation, experimentation and reporting "interesting" observations during extra planetary missions etc. From these application, we also get some higher order AI problems. For example, a robot self-navigating a planet, needs to plan and chart its course from point A to point B or a robot that is attempting to fix a leak in a nuclear reactor needs to identify the set of task to perform so that the leak is fixed.
The goal of ML is to assimilate known knowledge in an abstract form called models, and be able to predict certain unknowns for instances that will be seen in the future. For example, in an email spam classification task, the goal is to learn a model from a known set of emails that have been labeled as spam or not spam and be able to predict whether the new email that we just received is spam or not spam. Classification is just one concrete instantiation of ML goal. Clustering can be thought of as predicting cluster variables for future instances and Regression can be thought of as predicting function values for points that haven't been observed so far etc.
AI with its very specific application focus can use tools built in ML to achieve its goals. However, ML serves a much broader class of problems.
With these in mind, what you want to start from is entirely upto you. For example, if you want to build planet-navigating robots then you probably need to start from AI, learn about the various interesting problems involved in AI, see what kind of ML tools you will need to learn, come to ML learn those tools and go back to AI. However, if your interest lies in building the ML tools that serve a fairly broad class of problems many of which are relevant in the real world today [1], then you may want to start learning ML first.
Note that, both ML and AI are vast fields with many things to learn. Even though I suggest switching from ML to AI and AI to ML, it is not as easy as it might sound :-). Unless you know what you want to learn and how you plan to use it, you might be aimlessly going into and learning things, that may or may not be relevant to what you might want to do. Not that it is wrong, but, as humans, we have very limited time and we need to use it as efficiently as possible.
Machine learning is a scaled down version of A.I, crudely speaking.
Let me make it clear.
First the Objective part : There is a machine that needs to learn something, just like how a man can learn something. Now, just like how one can use different methods to learn : Some are very powerful methods to learn, some are less weaker methods; some methods require a lot of time and lot of effort, some are simple. Machines also have different methods to learn things.
A machine can learn based on simple and easy techniques like Machine learning. This is starting point for entry to A.I. But there can be much more complicated techniques like Abstraction, back-propagation etc. which help us identify and learn more difficult patterns.
At the heart of both is Pattern Recognition, which is the genesis of this entire field of A.I and M.L.
My suggestion is start with ML and then go for A.I.
which platforms helps in learning excel SQL and power bi
Hello,
Power BI is a collection of software services, apps, and connectors that collaborate to link, convert, and clean data into a data model and produce charts for data visualisation. Of all BI tools, Power BI is regarded as the industry leader in business analytics. This has led to an ongoing increase in the need for certified Power BI personnel across the majority of leading MNCs. Therefore, people who are knowledgeable with Power BI ideas and have experience using it may make a good living and have the opportunity to work for prestigious companies. PayScale estimates that the average annual salary for a BI developer is 512,800 rupees ($74,400) in India and the United States, respectively.
Alright! Joining Power BI online training is the finest option, if you're asking me what the best resources are for learning Microsoft Power BI. As a result of this BI tool's popularity, several institutions began providing training in Power BI. In partnership with IBM, Intellipaat is one of the well-known training companies for Power BI.
Thank You
