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Six months of AI and Data Science Mentorship Program

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About Course

Learn complete Data Science and AI in 6 months only.

Start Date: 01.10.2023

End Data: 31.03.2024

Pre-requisite: The whole python ka chilla 2023 for data science.

Follow our Whatsapp channel now, we will keep you updated here, Follow now for updates.

This will train you to have a job Ready Data Scientist

The plan is as follows:

  • You will register to this program
  • You will be added in discord server.
  • You will be added in WhatsApp group at the end of this registration process
  • You will be given 1–3 hours of lectures (recorded) every day for 5-6 days a week for whole duration of this program
  • The time of daily lectures is 09:30 pm Pakistan time live on our youtube channel www.youtube.com/@codanics
  • You will learn from those lectures and prepare assignments and tasks accordingly
  • 2-3 Zoom Meetings in a week, only on weekends (Around 9:30 pm Pakistan Time) only for Paid.
  • 1-to-1 Assignment Feedback (Only for Paid)
  • Certificates (only for Paid)
  • We are very strict about assignments, otherwise, you will be removed from the program.
  • Disables students/people are sponsored by Codanics for Zoom Meetings.

These are the aims and goals (bashart-e-zindage) of this program:

  1. Python Programming (Zero-Hero)
  2. Data Science/Analytics (Zero to advance)
  3. Mathematics (Zero to advance)
  4. Statistics (Zero to advance)
  5. Microsoft Excel (Zero to advance)
  6. Markdown Language (Zero to advance)
  7. SQL (Zero to advance)
  8. Machine Learning (Zero to advance)
  9. Deep Learning (Zero to advance)
  10. Time Series Analysis (Zero to advance)
  11. Transfer Learning
  12. Genertive AI
  13. Web App Development (Zero to advance)
  14. Web App Deployment (Zero to advance)
  15. NLP (Basics-Intermediate)
  16. Lang Chain Crash Course
  17. Software Development using Python (Basics)
  18. Web development using WordPress (Zero to advance)
  19. Web Development Using Flask/Fast API/Django (Zero to advance)
  20. Blogging (Zero to advance)
  21. Social Media Handling and Analysis (Zero to advance)
  22. How to earn Online using Data Science and AI (Zero to advance)
  23. Google AdSense Crash Course (Zero to advance)
  24. How to start a YouTube Channel? (Zero to advance)
  25. Much More to come and Surprises as well

if you have any questions, you may contact us at info@codanics.com 

visit us: www.codanics.com

Dear, to register for the 6 months AI and Data Science Mentorship Program, click this link and fill the form give there: https://shorturl.at/fuMX6

Join our WhatsApp channel for details and updates about recent positions:
https://whatsapp.com/channel/0029Va7nRDq3QxRzGqaQvS3r
Follow me on LinkedIn:
https://www.linkedin.com/in/aammar-tufail/
Tiktok:
https://www.tiktok.com/@draammar

Youtube: www.youtube.com/@codanics

Twitter/X: https://x.com/aammar_tufail

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What Will You Learn?

  • AI
  • Data Science
  • Mathematics
  • Statistics
  • Machine Learning
  • Deep Learning
  • Webapp development
  • Social media Handling
  • Prompt Engineering
  • Website making
  • and much more

Course Content

How and Why to Register
Dear, to register for the 6 months AI and Data Science Mentorship Program, click this link and fill the form give there: https://shorturl.at/fuMX6

Software installation and Important Details
In this section you will learn which software are important to install and learn from.

Day-1
Introduction and details about 6 months plan

Day-2
What is AI and How is it Different From Data Science?

Day-3

Day-4

Day-8
Master Pandas Library

Day-9

Day-10

Day-11

Day-12

Day-13

Day-14

Day-15

Day-17: Complete EDA on Google PlayStore Apps

Day-19: Complete EDA project on Apple APP store apps Dataset

Day-25: Quiz Time, Data Visualization-4

Day-27: Data Scaling/Normalization/standardization and Encoding

Day-28: NumPy (Part-1)

Day-29: NumPy (Part-2)

Day-30: NumPy (Part-3)

Day-31: NumPy (Part-4)

Day-32a: NumPy (Part-5)

Day-32b: Data Preprocessing / Data Wrangling

Day-33: Zero-to-Math for Data Science (Part-1)

Day-35: Zero-to-Math for Data Science (Part-3)

Day-36: Zero-to-Math for Data Science (Part-4)

Day-37: Algebra in Data Science

Day-41: Elementary Algebra

Day-42: Linear Algebra (Part-1)

Day-48: Linear Algebra (Part-7)- Solving System of Equations

Day-50: Linear Algebra (Part-9)- Solving System of Equations

Day-56: Statistics for Data Science (Part-5)

Day-58: Statistics for Data Science (Part-7)

Day-59: Statistics for Data Science (Part-8)

Day-60: Statistics for Data Science (Part-9)

Day-63: Statistics for Data Science (Part-12)

Day-65: Statistics for Data Science (Part-14)

Day-67: Machine Learning (Part-1)

Day-69: Machine Learning (Part-3)

Day-70: Machine Learning (Part-4)

Day-75: Machine Learning (Part-9)

Day-80: Machine Learning (Part-14)-Ensemble Algorithms

Day-81: Machine Learning (Part-15)-Evaluation Metrics

Day-82: Machine Learning (Part-16)-Metrics for Classification

Day-83: Machine Learning (Part-17)

Day-85: Machine Learning (Part-19)

Day-89: Machine Learning (Part-23)

Day-91: Machine Learning (Part-25)

Day-93: Machine Learning (Part-27)

Day-100: Un-Supervised Machine Learning (Part-1)

Day-104: Deep Learning (Part-2)

Day-114: Deep Learning (Part-11)-Convolutional Neural Network (CNN)

Day-115: Deep Learning (Part-12)-Convolutional Neural Network (CNN)

Day-116: Deep Learning (Part-13)-Computer Vision

Day-117: Deep Learning (Part-14)-Complete CNN Project

Day-118: Deep Learning (Part-15)-Recurrent Neural Network (RNN)

Day-119: Deep Learning (Part-16)-Natural Language Processing (NLP)

Day-120: Deep Learning (Part-17)-Natural Language Processing (NLP)

Day-121: Time Series Analysis (Part-1)

Day-123: Time Series Analysis (Part-3)

Day-126: Time Series Analysis (Part-6): Web-scrapping

Day-128: Time Series Analysis (Part-8): Complete Project

Day-129: git & GitHub Crash Course

Day-131: Improving Machine/Deep Learning Model’s Performance

Day-132: Transfer Learning and Pre-trained Models (Part-1)

Day-133: Transfer Learning and Pre-trained Models (Part-2)

Day-134 Transfer Learning and Pre-trained Models (Part-3)

Day-135: Generative AI (Part-1)

Day-136: Generative AI (Part-2)

Day-137: Generative AI (Part-3)

Day-139: Generative AI (Part-5)-Tensorboard

Day-140: Generative AI (Part-6)-Diffusion Models

Day-143: Huggingface

Day-145: Streamlit for webapp development and deployment (Part-1)

Day-146: Streamlit for webapp development and deployment (Part-2)

Day-147: Streamlit for webapp development and deployment (Part-3)

Day-148: Streamlit for webapp development and deployment (Part-4)

Day-149: Streamlit for webapp development and deployment (Part-5)

Day-150: Streamlit for webapp development and deployment (Part-6)

Day-151: Streamlit for webapp development and deployment (Part-7)

Day-152: Streamlit for webapp development and deployment (Part-8)

Day-153: Streamlit for webapp development and deployment (Part-9)

Day-154: Streamlit for webapp development and deployment (Part-10)

Day-155: Streamlit for webapp development and deployment (Part-11)

Day-156: Streamlit for webapp development and deployment (Part-12)

Day-157: Streamlit for webapp development and deployment (Part-13)

How to Earn using Data Science and AI skills

Day-158: Flask for web app development (Part-1)

Day-160: Flask for web app development (Part-3)

Day-161: Flask for web app development (Part-4)

Day-162: Flask for web app development (Part-5)

Day-163: Flask for web app development (Part-6)

Day-164: Flask for web app development (Part-7)

Day-165: Flask for web app deployment (Part-8)

Day-167: FastAPI (Part-2)

Day-168: FastAPI (Part-3)

Day-169: FastAPI (Part-4)

Day-170: FastAPI (Part-5)

Day-171: FastAPI (Part-6)

Day-172: FastAPI (Part-7)

Day-174: FastAPI (Part-9)

Day-177: Tableau Complete Course (Part-3)

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Student Ratings & Reviews

5.0
Total 2 Ratings
5
175 Ratings
4
8 Ratings
3
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0 Rating
1
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ZM
7 months ago
Great Course
ZM
7 months ago
Great Course