
Install Anaconda, set Python 3.9 as default, and launch Anaconda Navigator. Open Jupyter Notebook to create a Python 3 notebook and start coding.
Learn Jupyter Notebook basics, including creating notebooks like Untitled.ipynb, running code cells with run button, adding or deleting cells with plus and scissors, and switching between command and edit modes.
Learn to define variables in Python using the equals sign, print stored values, and work with integers, floats, strings, and booleans while noting comments, case sensitivity, and the execution flow.
Learn why you should never overwrite a built-in function or redefine variables in python, and how restarting the kernel and re-executing cells restores default behavior.
Explore typecasting in Python by converting between int, float, and string using built-in functions. See how booleans transform, how empty strings affect truth values, and how input captures user input.
Practice creating a Python program that reads user input, casts it to float, adds it using the plus sign, and prints the final output; for example, input 10 yields 20.0.
Explore arithmetic operators, including addition, subtraction, multiplication, division, exponential, and modulus, with examples using five and two to show remainders and how to test even numbers.
Highlight comparison operators such as equals and not equal, larger or smaller with their equal forms, and combine conditions using and and or to yield true or false results.
Explore Python conditional statements and indentation, using if, elif, and else blocks to print outcomes like 'price is high' or 'price is low' based on value comparisons.
Practice writing a Python program that takes two user inputs, converts them to floats, and prints which user provided the larger number or if they provided the same number.
Explore lists as a Python data type, create lists with square brackets, store mixed types, and use methods like append and index to modify and locate items with zero-based indexing.
Explore list indexing and slicing in Python using zero-based and negative indices, and understand the start-inclusive, stop-exclusive slice syntax with practical examples from presidents.
Explore how lists are mutable in python by indexing and reassigning elements, and contrast them with tuples, which are immutable and raise errors on item assignment.
Discover dictionaries as a mutable data type built with curly braces that map keys to values, allow access via keys, and updates such as Martin's amount from 100 to 50.
Explore for loops by iterating over lists and range objects, printing elements and performing operations like multiplying by two, filtering even numbers with modulus, and appending results.
Explore Python list comprehension: replace loops and append with a single-line [i for i in range(1,11)], filtering even numbers with a condition and multiplying results by two.
Explore the while loop by checking a condition and incrementing x each iteration; avoid endless loops and terminate when x reaches ten.
Practice building a Python shopping list program that collects three items via input and appends them using length method and while loop. Try for i in range(3) and list comprehension.
loop from 1 to 20 and check divisibility: print first if divisible by 15, then if divisible by 3, then if divisible by 5; otherwise print the number.
Learn to define functions with def, pass arguments, and use return to obtain values; understand printing vs returning, and local vs global variables when calling functions.
What is this course about?
In this course I am breaking down the most important fundamentals you need getting started with Python - or if you want to refresh your knowledge on the basics or try yourself out on one of the various coding tasks! :-)
Why should I be your constructor?
I got years of experience coding in Python and know which topics are key to understand to actually move on to topics like Data Analytics, Machine Learning, Data Science or Algorithmic Trading.
I wrote my Master Thesis on a quantitative Finance topic, currently working in the field of Data Science and got a YouTube channel teaching Algorithmic Trading and Data Science hands-on tutorials with over 50.000 subscribers.
I love coding & I love teaching :-)
Why this course?
This course is giving a rock solid foundation for anyone interested in learning Python in specific to apply it to above mentioned topics.
I am following an hands-on approach and provide a lot of quizzes and actual coding tasks (including solutions).
There is not a single time filler and we are getting straight into the topics.
Any questions coming up?
If you got any questions please feel free to reach out! I am happy to hear from you.