Executive PG Programme in Machine Learning and AI
Learn with us without quitting your job
Leading companies recruit upGrad learners
The right course for you aligns with your career goals
Our curriculum focuses on industry relevant skills
Best-in-class content by leading faculty and industry leaders with customised specialisations.
You can now study from home and pay less to do so!
On Campus Fees
+ No Incoming Salary for 1 year
for 12 months
Amount saved - USD 22,000 + 1 year salary and work experience
VP, Payments Portfolio, Citi Bank
Very happy that I joined the program, I joined the programme because I wanted to be future ready.LinkedIn Profile
Data Analyst, Bongo, Dhaka
I got a great career transition with almost 30% raise due to upGrad.LinkedIn Profile
Senior Software Engineer, Mindfire Solutions
You will be notified of any interview opportunities in ML and they will share your profile with the recruiters. This really helps to kick start your...Detailed Review
Machine Learning Engineer, AstraZeneca
This course puts you from a beginner level to a person who can understand and provide a machine learning solution to any given problem provided one...Detailed Review
Deep Learning Engineer, Samsung
Many of the basic concepts are being taught to build good intuition of Machine Learning models. Most of the basic maths required for developing an intuition...Detailed Review
Software Engineer, Tarant Software
A great aspect about this course are the student mentors. These people are always there to help, support, and motivate the student to complete modules on...Detailed Review
Your career growth is one application away
Step 1: Online eligibility test
Step 2: Shortlisting & offer letter
Step 3: Confirmation & prep-course
360 degree Career services provided to ensure your success!
Get mentored by an experienced ML & AI industry expert and receive personalised feedback with 1:1 mentorship sessions.
A career mentor to help you track your weekly job application targets, coach you on your profile and help you on your career transition journey.
Get company and role-specific preparation with mock interviews right before your actual interviews.
Learn from your peers through discussion forums, small group coaching sessions and a lot more activities.
IITM & LJMU
How do I know if this program is for me?
How will this program benefit me?
What is this program intended to do?
What can I expect out of this program?
What should I NOT expect from this program?
Is there any certification at the end of the program?
As AI continues to progress rapidly in 2021, achieving mastery over Machine Learning (ML) is becoming increasingly important for all the players in this field.
So, if you are a beginner, the best thing you can do is work on some Machine Learning projects. We have some great machine learning project ideas for you.
1. Stock price predictor Businesses today are on the lookout for software that can monitor and analyze the company performance and predict future prices of various stocks. And with so much data available on the stock market, it is a hotbed of opportunities for data scientists.
2. Sentiment Analyzer You can try to mine the data from Twitter or Reddit to get started with your sentiment analyzing machine learning project. This might be one of those rare cases of deep learning projects which can help you in other aspects as well.
3. Enhance healthcare By harnessing healthcare data, you can create diagnostic care systems that can automatically scan images, X-rays, etc., and provide an accurate diagnosis of possible diseases. Machine learning is still at an early stage throughout the world. There are a lot of Machine Learning projects to be done, and a lot to be improved.
Machine Learning is a subset of AI and is the scientific study of algorithms and statistical models used by computer systems. The primary aim is to allow computers to learn automatically, with no human intervention or assistance. Here are some key prerequisites for machine learning
1. Statistics, Calculus, Linear Algebra and Probability Statistics contain tools that are used to get an outcome from data. Calculus plays an integral role in the algorithm. Linear Algebra is used in machine learning to perform operations and transform on datasets. Furthermore, the probability is also a foundation in machine learning prerequisites.
2. Programming Knowledge: Writing code is one of the most important things when it comes to Machine Learning. You need to know languages such as Python and R to implement the process.
3. Data Modeling It is a process of estimating the structure of the data set, and it is done to find any variations or patterns within. Machine Learning is also based on predictive modelling. If you do meet these machine learning and AI prerequisites, understanding machine learning would become much easier.
AI is one of the most popular technologies on the planet, thanks to its versatility and advanced solutions. It has been growing at a fast pace, but what is the future scope of artificial intelligence? Today we take a look at the answer.
1. Science and research AI can handle large quantities of data and processes it quicker than human minds. This makes it perfect for research where the sources contain high data volumes. AI is already making breakthroughs in this field.
2. Cybersecurity is another field that’s benefitting from AI. As organizations are transferring their data to IT networks and the cloud, the threat of hackers is becoming more significant. Cognitive AI is an excellent example of this field.
3. Data analysis can benefit largely from AI and ML. AI algorithms are capable of improving with iterations, and this way, their accuracy, and precision increase accordingly. AI can help data analysts with handling and processing large datasets. As AI shows massive acceleration in these fields, AI and machine learning careers are also on a rise. This makes AI a highly lucrative field for professionals to invest in.