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Python AI Course

Python AI Course
from 4 to 360h flexible workload
certificate recognized by MEC

What will I learn?

Unleash the potential of AI with our Python AI Course, tailored for technology experts aiming for excellence in recommendation systems. Delve into both collaborative and content-based filtering strategies. Learn data collection and preparation using Pandas, and explore movie datasets. Strengthen your skills through exploratory data analysis employing Matplotlib and Seaborn, and build models using Python and NumPy. Understand how to assess and refine models using precision, recall, and the F1-score. Further learn to develop precise documentation and reports.(ብPython ዝተሃንጸ AI ትምህርቲ ኣቢልካ ናይ AI ዓቕሚታት ተግብር፣ ነቶም ኣብ system ምክሪ ብሉጻት ክኾኑ ዝደልዩ ናይ ቴክኖሎጂ ሰብ ሞያታት ዝዓለመ እዩ:: ብሓባር ኮይኖም ዝሰርሑን ኣብ ትሕዝቶ ዝተመስረቱ ናይ ምምራጽ ስልትታት መርምር:: Pandas ብምጥቃም ዳታ ናይ ምስባስን ናይ ምድላውን ኣገባብ ተምሃር፣ ከምኡ’ውን ናይ ፊልም ዳታታት ዳህስስ:: Matplotlibን Seabornን ብምጥቃም ክእለትካ ኣመሓይሽ፣ Pythonን NumPyን ብምጥቃም ሞዴላት ስራ:: ሞዴላት ብልክዕነት፣ ብምዝካርን ብF1-score ከመይ ገርካ ከም እትገምግምን ከም እተመሓይሽን ተገንዘብ:: ንጹርን ምቹእን ጸብጻብ ከመይ ገርካ ከም እተዳሉ ተምሃር::)

Elevify advantages

Develop skills

  • Master collaborative filtering: Enrich AI understanding through user-item interaction insights. (ብሓባር ናይ ምስራሕ መምረጽ ምሕያል:: AI ብዛዕባ ተጠቃሚን ንብረትን ዘለዎ ምትእስሳር ኣስተውዕሎትን ምሕያል::)
  • Clean and prepare data: Fine-tune datasets for pinpoint AI model training. (ዳታ ምጽራይን ምድላውን:: ንጹር ዝኾነ AI ሞዴል ንምስልጣን ዳታታት ምምሕያሽ::)
  • Visualize data insights: Use Matplotlib and Seaborn to craft compelling data narratives. (ናይ ዳታ ምርኣይ ኣስተውዕሎት:: Matplotlibን Seabornን ብምጥቃም ጽሑፍካ ምምስሳል::)
  • Evaluate models effectively: Employ precision, recall, and F1-score metrics wisely. (ሞዴላት ብውጽኢታዊ መንገዲ ምግምጋም:: ልክዕነት፣ ምዝካርን፣ F1-ሜትሪክስን ብጥበብ ምጥቃም::)
  • Document with clarity: Develop succinct reports enhanced with code examples and visuals. (ንጹር ጸብጻብ:: ዝተሓጠር ኮድ ምስ ምሳሌታትን ምስላዊ መግለጽታትን ምጥቃም ጸብጻብ ምምዕርራይ::)

Suggested summary

Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.
Workload: between 4 and 360 hours

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Very great course. Lots of rich information.
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