About Bootcamp

The advanced bootcamp on AI with focus on Deep Neural Networks (DNNs) aims to impart high impact knowledge and skillset to fresh graduates. Participants will become internationally competitive through 280 hours of intense hands-on training under the mentorship of industry leaders.

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Unique Features:

  • Industry-Relevant Curriculum: The Bootcamp’s curriculum is carefully designed to address the latest trends and demands of the computer science industry, ensuring that participants gain relevant and up-to-date knowledge.
  • Personalized Learning Experience: The bootcamp will offer one-on-one mentoring, ensuring participants receive individualized guidance and support throughout their learning journey.
  • Hands-On Project-Based Learning: Participants will engage in extensive hands-on learning through real-world projects, allowing them to apply the acquired skills in practical scenarios.
  • Expert Instructors from GIKI and Industry: The Bootcamp’s instructors come from reputable universities (FCSE, GIKI) and industry (SkyElectric, SkyLab), providing a rich learning experience with insights from both academia and the real-world industry.
  • Job Placement Assistance after Bootcamps: The bootcamp goes beyond training and offers job placement possibilities, connecting participants with potential employers and helping them kick start their careers in the field of computer science.


Weekly Modules:

  • Week 1: Introduction to AI and Applications in the Real World
  • Week 2: Machine Learning
  • Week 3: Fundamentals of Deep Neural Networks
  • Week 4: Computer Vision
  • Week 5: Sequence Modelling and Vision transformers
  • Week 6: Special Topics in Deep Learning and the Modern era of Generative AI
  • Week 7: Project Planning and Refinement
  • Week 8: Project Demos and Presentations Refinement

Eligibility Criteria:

  • Fresh graduates from HEC recognized universities seeking technical skills and job prospects.
  • Candidates must have graduated from HEC recognized universities with a BS or MS degree in any science, technology, engineering, or math (STEM) discipline or are going to graduate in 2024. (Students in their Junior year BS programs in STEM disciplines who fulfill the following eligibility criteria can also apply).
  • Proficient with Python programming.
  • Good foundation in mathematics especially Linear Algebra, Calculus, Probability and Statistics.
  • Good analytical and reasoning skills.
  • You are able to attend the bootcamp regularly at GIKI in Face-to-Face mode.
  • All applicants are required to pay an application processing fee of Rs. 500/- (non-refundable).
  • The candidates who are successful in the entry test and interviews will pay a subsidized registration fee of Rs. 20,000/-. The registration fee includes free on-campus accommodation at GIKI. Meals are not included.


Selection Procedure:

  • All applicants will take a computer based aptitude test at Virtual University Test Center of their choice
  • Entry Test Format:
    Duration120 Min
    Total Questions100
    Programming (Python)34%
    Analytical / Quantitative Reasoning33%
  • Shortlisted applicants will be required to appear in-person or online interview for final selection.

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Important Dates:

  • Registration Deadline: 20th June, 2024
  • Entry Test: 25th June, 2024
  • Interviews: Successful candidates will be informed via email about the interview date and time.
  • Bootcamp Duration: 8th July to 31st August, 2024

Schedule (Monday to Friday):

  • Classes: 8:30 am to 1:00 pm
  • Labs: 2:00 pm to 5:00 pm

Bootcamp Instructors:

Dr. Ali Imran SandhuAssistant ProfessorComputational Electromagnetics, Microwave Imaging, Physics Informed Machine Learning, Bayesian Experimental Design, Phased Array Antennas
Ph.D. Electrical Engineering, King Abdullah University of Science & Technology (KAUST), Saudi Arabia.
Engr. Dr. Muhammad HanifAssistant ProfessorImage Deconvolution, Sparse Image and Signal Representation, Image and Video Compression, Image Restoration, Registration and Segmentation, Object Detection and Tracking
Ph. D. Australian National University, Canberra (2015)
Dr. Sarah IqbalAssistant ProfessorIoT, Fog Computing, Machine Learning & Digital Twin
Doctor of Philosophy, Universiti Malaya, Kuala Lumpur, MALAYSIA.
Dr. Musadaq MansoorAssistant ProfessorMachine Learning, Deep Learning, Bio informatics, Software Engineering
Ph.D. in Computer Science National University of Computer and Emerging Sciences, (NUCES-FAST), Pakistan
Dr. Khurram Khan JadoonAssistant Professorcomputer vision, Image Processing, and Machine/deep learning
Ph.D. in Electronics and Communication Engineering
Mr. Muhammad Talha AshfaqLecturerArtificial Intelligence, Deep Learning, Data Analytics
MS (Computer Science)
Mr. Abdullah Bin ZarshaidLecturerIoT Security and Privacy, Software Defined Networking, Ethical Hacking, AI-Enabled Cybersecurity
MSc in Computer Networks and Security
Ms. Nazia ShahzadiLecturerMachine Learning, Deep Learning, Artificial Intelligence, Smart Grids, and Data Science
MS Cybersecurity


Lab Engineers:

Ms. Hifza UmerLab EngineerSoftware Engineering, Machine Learning, Deep Learning
BS Software Engineering, COMSATS University Islamabad, Attock Campus
Mr. AsimLab EngineerInformation Technology, Machine Learning, Deep Learning
BS Information Technology, University of Agriculture Peshawar
Ms. Memoona SaleemLab EngineerSoftware Engineering, Machine Learning, Deep Learning
BS Software Engineering, COMSATS University Islamabad, Attock Campus


Teaching Assitants:

Mr. Usama ArshadInstructorMachine Learning, Deep Learning
MS (Computer Science)


Advisory Board:

  • Mr. Ashar Aziz
    Chairman BedRock Systems, Inc., Chairman SkyElectric, Inc., Founder FireEye, Inc.
  • Lt Gen (R) Muhammad Asghar
    CEO – Qarshi Knowledge City, Former – Rector NUST
  • Prof. Dr. Fazal Ahmad Khalid
    Rector, GIKI
  • Prof. Dr. S. M. Hasan Zaidi
    Pro-Rector (Academic), GIKI
  • Prof. Dr. Qadeer ul Hasan
    Dean FCSE
  • Prof. Dr. Zahid Halim
    Coordinator DNN BootCamp
    Dean ODL & HoD (Computer Science & Artificial Intelligence)
  • Prof. Dr. Ghulam Abbas
    Overall Coordinator
    HoD (Software Engineering & Cyber Security)

Policy for Leaves, Attendance and Lab Participation

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