Machine Learning is one of the fastest growing fields in the world today and a Machine Learning Internship opens new and interesting opportunities for its participants.
This is what you will get from the Machine Learning Internship - A Chance to Transform your Career.
This Machine Learning Internship is a great way for you to start your data science career. It is designed to both test your knowledge and to give you the feel and experience of a real-world data science problem. Here is an overview of this 8-week internship.
There is a great demand for machine learning professionals across the world. According to news reports, 50,000+ data science jobs are vacant due to shortage of talent
As a result, you end up with an extremely large population of uncertified professionals competing for the high-paying machine learning jobs and Machine Learning Projects.
This Machine Learning internship will ensure that you get a leg up on the competition in the job market and get some real experience. Here are the reasons this machine learning internship can bring about a total transformation in your career.
You will have to do programming in Python and use machine learning libraries from Scikit-Learn (e.g., Pandas, Matplotlib, Seaborn etc). You will implement machine learning algorithms for Regression and Classification.
Eligibility
The Machine Learning Internship is meant for students who have a background, or are keen to learn, a programming language and solve business problems using AI/ML. It is ideal for students of Engineering (any discipline) or purely Computer Science. It can also be pursued by MBA students or anyone else in their postgraduate pursuits. Really, it's never too late to start learning about all this.
Application Process
Applying for the machine learning internship is a breeze. Just follow the simple steps give below to get started on your machine learning journey.
Intel® is our software and hardware partner for all of our data science programs.
Complete the internship and get certified from us along with Intel. Along with the physical certificate of completion, get a machine learning crash course.
The Machine Learning internship begins as soon as you enroll for it. You will get the login credentials of the dashboard. In this dashboard, you can view all the learning resources and the assignments, week-wise.
The internship can be completed in 8-weeks or in an even lesser duration. Once you submit your assignments, you would have completed the internship projects and your interview would get scheduled shortly after that. While it can be started on any date, college goers should look at doing this internship during their vacations.
Yes, all your weekly assignments will be checked by our panel of data science experts. Feedback will also be shared with you in case your assignment is not up to the expectation level.
You can ask your questions to our team of machine learning experts who will mentor you during this internship. All you need to do is write in a mail at analytics@careerlauncher.com.
The biggest and the most important point of difference is that this is an internship while those are courses. The biggest reasons why most students don't get the desired outcome out of the other courses is that those courses are only hours and hours of videos. In this internship, you code each week and, therefore, get the hands-on experience.
Just like any other internship, this internship brings to you an opportunity to learn things that are relevant to the industry. If you learn from this internship, you will be better that most job-seekers and therefore, finding a job should not be a challenge.
Here’s a demo of the learning resources that you would get during these 8 weeks. Register now for this demo and get access to the demo dashboard.
Access the DemoThe modules covered in the Machine Learning Internship can be thought of as Machine Learning Projects with a set objective that the participant has to complete every week. These Machine Learning projects require the participant to study on the relevant topics and practically apply it to solve each problem. Solving these problems will allow the participant to complete the module and move on to the next module and Machine Learning Project.
1. Plot the daily volumes of a given stock as well and compare the percentage stem plot to it. Document your analysis of the relationship b/t volume and daily percentage change.
2. Analyse the correlation between daily returns of any 5 stocks of your liking. This is extremely useful for a fund manager to design a diversified portfolio. To know more, check out these resources on correlation and diversification.
3. Plot the appropriate trade calls for the given stock data. Use 21 day and 34 day moving averages to get the appropriate predictions for the calls.
Have questions? Our international data science team is more than happy to take them:-
Arnav Gulati - 22agulati@berkeley.edu
