AI Online Internship
Internship program on projects in the area of Machine Learning and Artificial Intelligence

An internship is an opportunity to integrate career experiences into your college education. In a professional setting, an internship will give knowledge and skills related to your career goals by participating in strategic, supervised work.

Most good companies are looking for students with internship experience. Internships will give you a competitive advantage in the job market. It will also provide the entry-level skills, training necessary to better prepare you for a high growth career path.

You will be working with experts to

  • Implement the Research for at least one end customer
  • Conceptualize and Plan the Research and Product
  • Do Research and Data analysis for same
  • Write white papers etc
Duration: 40 Days Batch Size: 30 Students

Affordable Price

100% online

Real College Credit

No Application

What an intern will be doing ?

AI is a science that requires much skill and determination to gain expertise in. If you see yourself working for artificial intelligence jobs, then you need to have the basic educational qualification and skill set to get there.

Project on cutting edge AI Technologies such as Machine Learning, Deep Learning, Computer Vision, NLP and their real life applications. The field of work would span from AI enabled supply chain project, to chatbots, to face recognition, to building better educational tools using AI and deep learning.

Syllabus Structure

What you will learn from this course


Module 1 : Introduction to ML and AI
  • Machine Learning and Human Learning
  • Types of Machine learning
  • Machine Learning and Deep Learning
  • Machine Learning and Arti?cial Intelligence
  • Industrial Applications of ML and AI
    Exercise class: Students will present the
  1. Project objective
  2. Sources of data
  3. Discuss project related issues
Module 2 : Data Pre-processing and Analysis
  • Data Cleaning
  • Statistical properties of data and its relevance
  • Visualization of data
  • Feature Engineering: Feature extraction and Feature generation
    Exercise class: Students to present the result of:
  • Data pre-processing
  • Discuss related issues

Module 3 : Machine Learning Algorithms
  • Regression and ANN model
  • Classi?cation and confusion matrix
  • Clustering
  • Performance metric
    Exercise class: Students to present the result of
  1. ML algorithm
  2. discuss related issues
Module 4 : Model validation and hypothesis testing
  1. Final presentation of the project in prescribed format and discussion if required
    Exercise class: Students to present the result of
  1. Data pre-processing
  2. ML algorithm
  3. Validation and hypothesis testing

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Most Vitti Research Foundation courses run multiple times. Every run of a course has a set start date but you can join it and work through it after it starts.

01 July, 2020
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