Virtual Summer Internships 2020

Get Certified in ML (Machine Learning) by Cognifront to accelerate your career

About Virtual Internship

Virtual internship is also called Online, Remote or Work-from Home Internship. Virtual Internship is done entirely via Internet and the Computer. Tools and Technologies like audio/video conferencing, social media, mail etc. are used for communication, collaboration and interaction. Embarking on a virtual internship is one of the best ways to build technology skills. In the wake of COVID-19, companies around the world are quickly changing their working patterns. Leading companies across the globe are increasingly turning to remote working. In fact, this trend has been seen for years but is now accelerating rapidly due to external factors like COVID-19 and climate change. The labour market now demands talent that thrives in a remote environment. Therefore, Virtual Internship is rising in popularity. It provides a great deal of flexibility of working at any-time and any-where without making long travel to the companies and finding accommodations at remote places. You simply gain professional work experience and complete the Internship from the comfort of your home.

Benefits of Virtual Internship

These days, many companies provide work-from home facilities to their employees. This mode of working saves travel time and cuts lot of cost in maintaining office infrastructure. Also, working in homely environment enables employees to produce quality work.

To help students to work in such companies, Cognifront has gathered best practices for the virtual internship. Using these strategies and tools will help students gain an effective summer internship experience.

These are just a few of the benefits you gain from virtual internship:

  • Develop your employability skills and help grow your career path by getting involved in a structured work experience opportunity
  • Advance your knowledge and skills of new technology & software as well as gain remote working skills
  • Develop your initiative, self discipline and time management skills
  • Increase your confidence and resilience
  • Engage in a flexible working pattern
  • It is flexible and fits around your existing work and studies
  • No expensive of travel or accommodation
  • Foster an understanding of virtual work trends across industries
  • Gain familiarity with a virtual work structure, including tools and techniques to manage responsibilities and share information

About Machine Learning and Artificial Intelligence

Data has become the Fuel for driving exponential growth of businesses and industries. Machine Learning (ML) and Artificial Intelligence (AI) churn out the massive volume of data and provide real-time insight for making data-driven decisions in companies.

As a result, new job opportunities are emerging. Career in ML and AI has become the sexiest job of the 21st century. Company giants like Microsoft, Intel, Facebook, Amazon, MATLAB, IBM, Tesla, Uber, GE, Google are vigorously working in the ML/AI fields. This has resulted in high demand for ML skilled manpower.

By the year 2020, according to Gartner Report, 23,00,000 jobs will be created in Artificial Intelligence and allied technological sectors.

Take the mystery out of Machine Learning and learn what it’s like to produce business results with the Cognifront Virtual Internship Program.

It is now time to become ML Smart and Job Ready by getting certified from Cognifront.

Virtual Internship Highlights

Technology Domain Machine Learning & Artificial Intelligence
Dates 15th May to 15th June 2020 (Batch-1)
5th June to 5th July 2020 (Batch-2)
10th June to 25th June 2020 (Batch-3)
30th June to 30th July 2020 (Batch-4)
Duration 30 Days (Batch-1, Batch-2, Batch-4)
15 Days (Batch-3)
Learning Hours 50 Hours
Computing Requirements Students should have their own DeskTop or Laptop or Mobile phone with Internet Pack
Fees (including GST) Rs. 450 per student
Alumni Discount Rs. 50 discount in Fees if a student has completed any course earlier with Cognifront
Payment Modes

Option A : Online Payment through Cognifront Website

Option B : Google Pay / Paytm to 9730045145

Option C : Net-Banking (Electronic Funds Transfer, NEFT/RTGS)

The Bank account details are as below:


Refund of Fees Fees are NOT refundable
Selection of Candidates Seats are limited. Hence, admissions are given on first come first serve basis
Coding Assignments 20
Case Studies 14
Project 1 Capstone Project
Self-paced videos 30+
Webinars 15+
Discussion Forum For interaction and doubt clearing
Interview Questions Practice on problems asked by top companies
Mentors, Trainers and Instructors Dr. R S Tiwari, PhD
Mr. Suchit Tiwari, MS (Computer)
Mrs. Meghana Tiwari, MSc (Computer)
Ms. Preeti Dambre, MSc (Computer)
Ms. Pooja Waghchoure, MSc (Computer)
Ms. Anita Mahale, BE (E&TC)
Mrs. Sushama Patil, BSc (Computer)
Certification Certificate of Internship will be issued by Cognifront on successful completion of Internship and Training activities
Contact for further details Website:
phone: 9422245764


  1. Fundamentals of Machine Learning and AI
  2. Applications of ML and AI
  3. Foundations of Python Programming
  4. Essentials of Statistics
  5. Setting up Python Ecosystem(Pandas, NumPy, Scikit, Collab) for ML
  6. ML Development Life Cycle
  7. ML Problem Formulation
  8. Data Acquisition and Feature Engineering
  9. Exploratory Data Analysis
  10. Data Visualization and Plotting using Matplotlib
  11. Data Pre-processing
  12. “Hello World” program of Machine Learning
  13. Linear Regression
  14. Logistic Regression
  15. Decision Trees
  16. Random Forests
  17. KNN
  18. K-Means Clustering
  19. SVM
  20. Artificial Neural Network
  21. Cross-Validation
  22. Evaluation Metrics
  23. Hyper parameter Tuning
  24. Introduction to ML Deployment
  25. Practice with Case Studies
  26. Hands-On Capstone Project

Select Your Batch

Batch - 1 from 15-May to 15-June 2020

Apply in Batch - 1

Batch - 2 from 5-June to 5-July 2020

Apply in Batch - 2

Batch - 3 from 10-June to 25-June 2020

Apply in Batch - 3

Batch - 4 from 1-July to 31-July 2020

Apply in Batch - 4

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