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Python Beginner Friendly Bestseller

Python for Machine Learning

Master Python fundamentals and apply them to real ML problems. Covers NumPy, Pandas, Scikit-learn, and neural network basics with hands-on projects and quizzes throughout.

DEMO VIEW:

⭐ 4.9

2,841 ratings

48

Lessons

12

Quizzes

12h

Duration

4.1k

Students

What you'll learn

✅ Python fundamentals & OOP

✅ NumPy & Pandas for data

✅ Scikit-learn pipelines

✅ Classification & regression

✅ Neural networks with Keras

✅ Model evaluation & tuning

Course Curriculum

📦 Module 1: Python Foundations 8 lessons · 2h

✓

Intro to Python Syntax

Lesson

18m

✓

Data Types & Variables

Lesson

22m

Q

Module 1 Quiz

Quiz · 10 questions

Score: 92%

📊 Module 2: Data with NumPy & Pandas 10 lessons · 3h

13

NumPy Arrays — Current

Lesson

25m

14

Pandas DataFrames

Lesson

30m

Python for ML

32/48 lessons

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Intro to NumPy

Lesson · 20m

✓

Array Operations

Lesson · 18m

13

NumPy Arrays

Lesson · 25m

14

Pandas DataFrames

Lesson · 30m

15

Data Filtering

Lesson · 22m

Q

Module 2 Quiz

Quiz · 12 questions

Module 3 — ML Fundamentals

18

Scikit-learn Basics

Lesson · 28m

19

Train/Test Split

Lesson · 15m

NumPy Arrays — Creating and Manipulating

📖 Lesson 13⏱ 25 min read🧩 Module 2

NumPy is the foundation of scientific computing in Python. At its core is the ndarray — an efficient, multi-dimensional array structure that enables fast numerical operations.

💡 KEY CONCEPT

Unlike Python lists, NumPy arrays are homogeneous (all elements have the same type) and stored in contiguous memory, which makes them orders of magnitude faster for numerical operations.

Creating Arrays

The most common way to create a NumPy array is with np.array(), passing a Python list or nested lists:

Pythonimport numpy as np

# 1D array from a list
arr = np.array([1, 2, 3, 4, 5])
print(arr)         # [1 2 3 4 5]
print(arr.dtype)   # int64
print(arr.shape)   # (5,)

# 2D array (matrix)
matrix = np.array([[1,2,3],[4,5,6]])
print(matrix.shape)  # (2, 3)

Useful Creation Functions

Pythonnp.zeros((3, 4))     # 3×4 matrix of 0.0
np.ones((2, 3))      # 2×3 matrix of 1.0
np.eye(4)           # 4×4 identity matrix
np.arange(0, 10, 2) # [0 2 4 6 8]
np.linspace(0, 1, 5) # [0.  0.25  0.5  0.75  1.]
np.random.rand(3, 3) # 3×3 uniform random [0,1)

⚠ WATCH OUT

When you assign an array to a new variable with b = a, both variables point to the same underlying data. Use b = a.copy() to get an independent copy.

Lesson 13 of 48

Student Quiz Scores

Python for Machine Learning · 4,127 enrolled

78%

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Quizzes Taken

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Pass Rate ≥70%

Good

315

Need Attention <50%

Score Distribution

0-50

51-60

61-70

71-80

81-90

91-100

Performance by Quiz

Module 1 Quiz84%

Module 2 Quiz78%

Module 3 Quiz71%

Final Exam62%

Student	M1 Quiz	M2 Quiz	M3 Quiz	Avg	Status
AJ Alex Johnson [email protected]	92%	78%	—	85%	On Track
MK Maria Kim [email protected]	96%	91%	88%	92%	Excellent
JD James Doe [email protected]	58%	44%	—	51%	Needs Help
SL Sara Lee [email protected]	88%	75%	72%	78%	On Track

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Python for Machine Learning

PythonBeginnerPublished

48 lessons · 12 quizzes · 4,127 students · ⭐ 4.9

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Kubernetes Fundamentals

DevOpsIntermediateDraft

32 lessons · 8 quizzes · 0 students · Not published

#	Title	Module	Type	Duration	Status
01	Intro to Python Syntax	Module 1	Lesson	18m	Published
02	Data Types & Variables	Module 1	Lesson	22m	Published
13	NumPy Arrays	Module 2	Lesson	25m	Draft

Quiz Name	Module	Questions	Pass Score	Attempts	Avg Score	Actions
Module 1 Quiz	Module 1	10	70%	3,821	84%
Module 2 Quiz	Module 2	12	70%	2,915	78%

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Tue

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Students — 42,810 (97.0%)

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Top Courses by Enrollment

Python for Machine Learning4,127

Advanced React Patterns3,802

Web App Security3,214

Kubernetes Fundamentals2,980

Platform Health

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Course Completion Rate68%

Quiz Pass Rate81%

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44,278 users total

User	Email	Joined	Current Role	Status
AJ Alex Johnson	[email protected]	Jan 15, 2025	Student	Active
JD James Doe	[email protected]	Mar 2, 2025	Student	Active
TB Tomas Bern	[email protected]	Nov 3, 2024	Teacher	Active
MK Maria Kim	[email protected]	Aug 22, 2024	Student	Suspended

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Learn to buildthe future

Python for Machine Learning

NumPy Arrays — Creating and Manipulating

Creating Arrays

Useful Creation Functions

Module 2 Quiz

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