Course Content
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Day-17: Complete EDA on Google PlayStore Apps
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Day-25: Quiz Time, Data Visualization-4
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Day-27: Data Scaling/Normalization/standardization and Encoding
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Day-30: NumPy (Part-3)
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Day-31: NumPy (Part-4)
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Day-32a: NumPy (Part-5)
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Day-32b: Data Preprocessing / Data Wrangling
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Day-37: Algebra in Data Science
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Day-56: Statistics for Data Science (Part-5)
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Day-69: Machine Learning (Part-3)
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Day-75: Machine Learning (Part-9)
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Day-81: Machine Learning (Part-15)-Evaluation Metrics
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Day-82: Machine Learning (Part-16)-Metrics for Classification
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Day-85: Machine Learning (Part-19)
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Day-89: Machine Learning (Part-23)
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Day-91: Machine Learning (Part-25)
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Day-93: Machine Learning (Part-27)
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Day-117: Deep Learning (Part-14)-Complete CNN Project
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Day-119: Deep Learning (Part-16)-Natural Language Processing (NLP)
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Day-121: Time Series Analysis (Part-1)
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Day-123: Time Series Analysis (Part-3)
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Day-128: Time Series Analysis (Part-8): Complete Project
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Day-129: git & GitHub Crash Course
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Day-131: Improving Machine/Deep Learning Model’s Performance
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Day-133: Transfer Learning and Pre-trained Models (Part-2)
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Day-134 Transfer Learning and Pre-trained Models (Part-3)
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Day-137: Generative AI (Part-3)
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Day-139: Generative AI (Part-5)-Tensorboard
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Day-145: Streamlit for webapp development and deployment (Part-1)
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Day-146: Streamlit for webapp development and deployment (Part-2)
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Day-147: Streamlit for webapp development and deployment (Part-3)
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Day-148: Streamlit for webapp development and deployment (Part-4)
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Day-149: Streamlit for webapp development and deployment (Part-5)
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Day-150: Streamlit for webapp development and deployment (Part-6)
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Day-151: Streamlit for webapp development and deployment (Part-7)
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Day-152: Streamlit for webapp development and deployment (Part-8)
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Day-153: Streamlit for webapp development and deployment (Part-9)
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Day-154: Streamlit for webapp development and deployment (Part-10)
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Day-155: Streamlit for webapp development and deployment (Part-11)
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Day-156: Streamlit for webapp development and deployment (Part-12)
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Day-157: Streamlit for webapp development and deployment (Part-13)
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How to Earn using Data Science and AI skills
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Day-160: Flask for web app development (Part-3)
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Day-161: Flask for web app development (Part-4)
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Day-162: Flask for web app development (Part-5)
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Day-163: Flask for web app development (Part-6)
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Day-164: Flask for web app development (Part-7)
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Day-165: Flask for web app deployment (Part-8)
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Day-167: FastAPI (Part-2)
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Day-168: FastAPI (Part-3)
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Day-169: FastAPI (Part-4)
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Day-170: FastAPI (Part-5)
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Day-171: FastAPI (Part-6)
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Day-174: FastAPI (Part-9)
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Six months of AI and Data Science Mentorship Program
    Join the conversation
    shariq ismail 3 months ago
    25
    Reply
    Muneer Ahmed 4 months ago
    25
    Reply
    Muhammad Faizan 11 months ago
    0.5+1+1.5+2+2+3+3+4.5+5 median will be the middle value of our sorted array or list of numbers which is "2".
    Reply
    Muhammad Faizan 11 months ago
    2+5+10+20+30+50+60+90 --> number of values=8/2= 4. So we will take only the middle 2 values 20 and 30 having index 4,5. take an average of them 20+30/2=50/2 -->25 ... So, he Median is 25.
    Reply
    Syed Abdul Qadir Gilani 12 months ago
    4.5
    Reply
    Syed Abdul Qadir Gilani 12 months ago
    50
    Reply
    Rana Anjum Sharif 12 months ago
    0.5,1,1.5,2,2,3,3,4.5,5 so median is 2
    Reply
    Rana Anjum Sharif 12 months ago
    10,20,30,50,52,60,90 so the median is 50
    Reply
    Liaqat Ali 1 year ago
    20
    Reply
    Waqas Ejaz 1 year ago
    30 , 20, 10 , 50, 60 , 10, 90, 5, 2Now first of all we convert it into ascending order 2, 5, 10, 10, 20 , 30, 50, 60, 9020 is the median.
    Reply
    Waqas Ejaz 1 year ago
    2, 5, 10, 20 , 30, 50, 60, 9020+30/2 = 25
    Waqas Ejaz 1 year ago
    2, 5, 10, 10, 20 , 30, 50, 60, 90 Now the median is 20
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