Introducing Algorithms in Python

with Muhammad Ateeq
4.5/5
(4)

Explore essential algorithms in Python! Learn searching (Linear & Binary), sorting (Bubble, Insertion, Merge, Quick), and complexity analysis (Big O notation). Understand efficiency, recognize trade-offs, and build a strong foundation for developing optimized algorithms in data science, software development, and coding interviews.

2 hours of content 101 students

$99.00

Lifetime access

Buy now
14-Day Money-Back Guarantee

What you get:

  • 2 hours of content
  • 17 Interactive exercises
  • 8 Coding exercises
  • World-class instructor
  • Closed captions
  • Q&A support
  • Future course updates
  • Course exam
  • Certificate of achievement

Introducing Algorithms in Python

A course by Muhammad Ateeq

$99.00

Lifetime access

Buy now
14-Day Money-Back Guarantee

What you get:

  • 2 hours of content
  • 17 Interactive exercises
  • 8 Coding exercises
  • World-class instructor
  • Closed captions
  • Q&A support
  • Future course updates
  • Course exam
  • Certificate of achievement

$99.00

Lifetime access

Buy now

$99.00

Lifetime access

Buy now
14-Day Money-Back Guarantee

What you get:

  • 2 hours of content
  • 17 Interactive exercises
  • 8 Coding exercises
  • World-class instructor
  • Closed captions
  • Q&A support
  • Future course updates
  • Course exam
  • Certificate of achievement

What You Learn

  • Understand algorithms and pseudocode, including their purpose, structure, and representation.
  • Master Linear and Binary Search, recognizing when each is most efficient.
  • Analyze algorithm complexity using Big-O notation to compare performance.
  • Implement Bubble, Insertion, Merge, and Quick Sort while understanding their trade-offs.
  • Identify the right algorithm for a problem based on efficiency and application.
  • Build a strong foundation for problem-solving, relevant to programming and data-driven tasks.

Top Choice of Leading Companies Worldwide

Industry leaders and professionals globally rely on this top-rated course to enhance their skills.

Course Description

Programming has two essential parts: devising logic (algorithms) to solve problems using relevant data (data structures). In data science, efficient algorithms and appropriate data structures are crucial for effectively processing and analyzing large datasets. This Introducing Algorithms in Python course bridges these fundamental concepts of algorithms.

In this Algorithms in Python course, you'll start by immersing yourself in the world of algorithms. You’ll learn how to think critically and develop efficient solutions through essential searching techniques like linear search and binary search, as well as fundamental Python sorting algorithms—including bubble sort, insertion sort, merge sort, and quick sort. Implementing these algorithms in Python will enhance your coding proficiency and problem-solving skills, which are vital in data science.

By the end of our Introducing Algorithms in Python course, you'll have a solid foundation to tackle data science projects more effectively—equipped with the skills to write efficient code to handle varying data proficiently.

Are you an aspiring data scientist, programmer, or someone looking to strengthen your fundamentals? This Algorithms in Python course provides the knowledge to advance your skills and confidence in recognizing and developing efficient solutions and applications.

Start mastering essential algorithms in this Introducing Algorithms in Python Course today!

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Welcome to the Course

1.1 Welcome to the Course

3 min

What Are Algorithms?

1.2 What Are Algorithms?

2 min

Algorithms vs. Code

1.4 Algorithms vs. Code

1 min

Summary

1.6 Summary

1 min

Interactive Exercises

Practice what you've learned with coding tasks, flashcards, fill in the blanks, multiple choice, and other fun exercises.

Practice what you've learned with coding tasks, flashcards, fill in the blanks, multiple choice, and other fun exercises.

true-false exercise
single-choice exercise
multiple-choice exercise
flashcards exercise
fill-blank-typing exercise
fill-blank-selection exercise
order exercise
categorize exercise

Curriculum

  • 1. Intro to Algorithms
    4 Lessons 7 Min
    • Understand what algorithms are, why they are fundamental in computing, and how they solve problems.
    • Learn to write pseudocode to express logic clearly and systematically.
    • Develop a structured problem-solving mindset applicable across programming and real-world challenges.
    Welcome to the Course
    3 min
    What Are Algorithms?
    2 min
    Algorithms vs. Code Read now
    1 min
    Summary Read now
    1 min
  • 2. Search Algorithms
    8 Lessons 17 Min
    • Master Linear and Binary Search, understanding their strengths and limitations.
    • Gain an intuitive grasp of efficiency—how different search strategies perform as data grows.
    • Learn to choose the best search approach for different types of datasets and applications.
    Introduction Read now
    1 min
    Linear Search Read now
    2 min
    Linear Search Implementation Read now
    2 min
    Analyzing Linear Search Read now
    4 min
    Sorted Data and Binary Search Read now
    3 min
    Binary Search Implementation Read now
    2 min
    Analyzing Binary Search Read now
    2 min
    Summary: Search Algorithms Read now
    1 min
  • 3. Analyzing Algorithm Complexity
    5 Lessons 15 Min
    • Understand how input size affects performance and why some algorithms scale better than others.
    • Explore the growth of functions and how they influence execution time.
    • Learn Big-O notation intuitively, using real-world analogies and comparisons.
    Introduction to analyzing algorithm complexity Read now
    4 min
    Formalizing Big O Notation Read now
    2 min
    Best, Average, and Worst Case Read now
    3 min
    Fundamental Complexity Classes Read now
    5 min
    Summary - Analyzing algorithm complexity Read now
    1 min
  • 4. Sorting Algorithms - I
    5 Lessons 27 Min
    • Discover why sorting is fundamental for organizing, retrieving, and optimizing data.
    • Learn how Bubble Sort and Insertion Sort work step by step.
    • Compare their efficiency and understand where they are practical despite being slow.
    Introduction - Sorting Algorithms - I Read now
    4 min
    Naive Sorting: Bubble Sort Read now
    13 min
    Visualizing Complexity Growth: From Constant to Quadratic Read now
    2 min
    Naive Sorting: Insertion Sort Read now
    7 min
    Summary - Sorting Algorithms - I Read now
    1 min
  • 5. Sorting Algorithms - II
    7 Lessons 38 Min
    • Explore recursion as an alternative to iteration, forming the foundation for efficient sorting.
    • Master Merge Sort and Quick Sort, understanding their divide-and-conquer strategies.
    • Learn when to use Merge Sort for stability and Quick Sort for speed and in-place efficiency.
    Introduction - Sorting algorithms - II Read now
    6 min
    Merge Sort Read now
    8 min
    Complexity of Merge Sort Read now
    4 min
    Quick Sort Read now
    10 min
    Complexity of Quick Sort Read now
    7 min
    Summary - Sorting algorithms - II Read now
    1 min
    You Did It!
    2 min

Topics

PythonAlgorithmsProblem SolvingAlgorithms ComplexitySearch AlgorithmsSorting AlgorithmsBig O-NotationProgramming

Tools & Technologies

python

Course Requirements

  • Basic Python knowledge
  • No prior experience needed in algorithms or data structures
  • Willingness to learn and engage

Who Should Take This Course?

Level of difficulty: Beginner

  • Early-stage programmers looking to build a solid foundation in algorithms.
  • Students and self-learners who want to master searching, sorting, and complexity analysis.
  • Aspiring data scientists and engineers seeking essential algorithmic skills.
  • Developers looking to improve problem-solving abilities for coding interviews and real-world applications.
  • Anyone curious about how algorithms work and how to apply them effectively.

Exams and Certification

A 365 Data Science Course Certificate is an excellent addition to your LinkedIn profile—demonstrating your expertise and willingness to go the extra mile to accomplish your goals.

Exams and certification

Meet Your Instructor

Muhammad Ateeq

Muhammad Ateeq

University of Leicester

1 Courses

5 Reviews

101 Students

I hold a PhD in Computer Science and have spent over 16 years in academia, teaching courses in Algorithms, Programming, Machine Learning, and Systems while mentoring students in research and applied problem-solving. My research includes QoS optimization in IoT, securing funding for experiments through FED4FIRE+ (An EU H2020 Project), and exploring AI-driven network efficiency. I have also worked as a Mentor at Udacity, guiding global learners in AI and Data Science. Through my teaching and mentoring, I tend to ensure that students develop both theoretical depth and practical problem-solving skills. I am committed to bridging theory and practice, making data-driven decision-making accessible, and equipping learners with the skills to excel in AI, software engineering, and beyond.

See More

What Our Learners Say

Osman Alenbey
Osman Alenbey
24.03.2025
Benson Muchoki
Benson Muchoki
21.03.2025

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