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برمجة الحاسب ببايثون 1
كلية الحاسب 47
الشابتر الأول
2h 0m
1
مقدمة والمخرجات
12m
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2
المتغيرات
10m
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3
انواع البيانات
10m
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4
المدخلات
11m
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5
شرح السلايدات النظرية
59m
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6
اسئلة تدريبية للشابتر الاول
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7
شرح اللاب الأول
18m
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الشابتر الثاني
1h 52m
1
المتغيرات
17m
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المتغيرات وانواع البيانات
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3
العمليات
26m
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الشروط
35m
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الشروط
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6
اسئلة تدريبية للشابتر الثاني
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7
شرح اللاب الثاني
27m
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اللاب الاول د سعيد
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الشابتر الثالث
1h 44m
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while loop #1
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while loop #2
9m
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for
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break & continue
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اللوب
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6
شرح اللاب الثالث
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اللاب الثاني د سعيد
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الواجب الأول
25m
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الشابتر الرابع
1h 36m
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مقدمة والدوال الجاهزة
18m
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الباراميترز
20m
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الريتيرن
10m
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السكوب
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الريكيرجن
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الدوال
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7
شرح لاب 4
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شرح لاب 4 اكسترا
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الشابتر الخامس
1h 18m
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سلايدات Lists #1
29m
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سلايدات Lists #2
25m
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شرح اللاب
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List
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الشابتر السادس
55m
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tuple
12m
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set
7m
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Tuples & Sets
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4
شرح تاسكات اللاب
18m
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شرح تشالنج اللاب
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الشابتر السابع
1h 21m
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الشرح #1
19m
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الشرح #2
24m
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شرح اللاب
38m
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Dictionary
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الشابتر الثامن
1h 15m
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الملفات #1
27m
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الملفات #2
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التعامل مع الأخطاء
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شرح اللاب الثامن
17m
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files
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المشروع
1h 5m
1
شرح المشروع
1h 5m
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الشابتر التاسع
1h 53m
1
مقدمة numpy
41m
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الجزء الثاني
50m
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شرح اللاب
22m
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numpy الكامل
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الشابتر العاشر
1h 34m
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Seris
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DataFrame
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filtering and exporting
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statistics
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شرح اللاب
17m
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pandas الكامل
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نماذج العملي
34m
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نموذج 45
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شرح نموذج 45
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نموذج 46 #1
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نموذج 46 #2
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الشابتر الحادي عشر
51m
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شرح الشابتر exceptions
51m
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exception handling
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الشابتر الثاني عشر
42m
1
الشرح
42m
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Specialized Domains
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الشابتر المختصر
1h 27m
1
مقدمة ل numpy
25m
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اكواد numpy
31m
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pandas
31m
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numpy + pandas المختصر
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تدريبات الفاينل النظري
1h 39m
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فاينل 46 #1
39m
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فاينل 46 #2
38m
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فاينل 46 #3
22m
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فاينل 46
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Week 10: Dictionary and Lists
59m
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Dict الشابتر العملي
23m
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List
36m
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Dictionary and Lists
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برمجة الحاسب ببايثون 1
كلية الحاسب 47
numpy + pandas المختصر
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50
NumPy arrays and Python lists have identical memory usage.
NumPy arrays are more memory-efficient because they store data in a continuous block of memory.
Python lists are faster because they don't require importing an external library.
NumPy arrays use more memory because they store additional metadata for every element.
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