- Master critical data science skills
- Learn data science and machine learning with Python
- Understand Machine Learning from top to bottom
- Learn NumPy for numerical processing with Python
- Learn Pandas for data manipulation with Python
- Explore machine learning models as interactive APIs
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Offer Curriculum
1 - BONUS Python Crash Course
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- 1 - Variables in Python (4:35)
- 2 - Conditionals If statement (4:49)
- 3 - Example for If statement (3:36)
- 4 - If else statement (2:02)
- 5 - Example of If else statement (1:51)
- 6 - Nested If statement (3:31)
- 7 - Example for Nested If statement (3:51)
- 8 - Elif statement (3:40)
- 9 - Example for Elif statement (2:24)
- 10 - While loop (6:52)
- 11 - Example of while loop (3:16)
- 12 - For Loop (7:37)
- 13 - Example of For Loop (1:56)
- 14 - Break Continue Statement (2:37)
- 15 - Introduction to containers (17:31)
- 16 - Creating and accessing lists in Python (7:06)
- 17 - List indexing and slicing (9:05)
- 18 - Working with List methods (31:05)
- 19 - Working with operators on lists (3:37)
- 20 - List Comprehension (3:57)
- 21 - Tuple definition (3:35)
- 22 - Tuples (3:08)
- 23 - Tuple Indexing Slicing (18:15)
- 24 - Manipulating Tuples (4:55)
- 25 - Unpacking Tuples (1:09)
- 26 - Sets (3:48)
- 27 - Dictionaries (5:32)
- 28 - Basics of dictionary (20:13)
- 29 - Accessing dictionary (7:16)
- 30 - len str type functions in dictionary (4:15)
- 31 - Functions in python (4:28)
- 32 - Example program1 on Functions (6:20)
- 33 - Example program2 on functions (3:21)
2 - Data Handling using Numpy
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days
days
after you enroll
- 34 - Introduction to modules in python (2:28)
- 35 - Creating Displaying 1D array (1:12)
- 36 - Understanding 1D array Index (4:17)
- 37 - Creating Array of 0s and Array of 1s (1:49)
- 38 - Sorting elements in 1D array (1:17)
- 39 - Slicing a 1D array (10:29)
- 40 - Mathematical Operations on Array (4:22)
- 41 - Searching an element in a Array (6:34)
- 42 - Filtering an array (4:20)
- 43 - Checking whether given array is empty or not (2:55)
- 44 - Creating Displaying 2D array (1:03)
- 45 - ndim Attribute (2:19)
- 46 - Size Attribute (2:30)
- 47 - Shape and reshape of array (3:17)
- 48 - Creating an Identity Matrix (2:19)
- 49 - arange (2:44)
- 50 - linspace (1:29)
- 51 - Random array (1:22)
- 52 - Random matrix (1:17)
- 53 - Creating a diagonal matrix (1:04)
- 54 - Flatten a Matrix (2:11)
- 55 - Computing Trace of a Matrix (3:12)
- 56 - Finding Transpose of a Matrix (4:19)
- 57 - Negative indexing to access elements in a 2D array (3:27)
3 - Data Handling using Pandas
Available in
days
days
after you enroll
- 59 - Working with series in Pandas (8:07)
- 58 - Introduction to Pandas (4:47)
- 60 - Combining series with Numpy (5:36)
- 61 - Finding number of elements in a series (1:30)
- 62 - Computing mean max and min in a series (3:38)
- 63 - Sorting a Series (2:49)
- 64 - Displaying Unique values in a Series (2:30)
- 65 - Summary of series statistics (2:12)
4 - Data Visualization using Matplotlib in Python
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days
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5 - Data Visualization using Seaborn in Python
Available in
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