Python Programming Session 1 (Operators,Variables, Data types )

Learn all core Python concepts and along the way, code your way through embedded exercises, to make coding intuitive. You will also be working with two Kaggle (Kaggle is world’s largest online Data Science community and a Google company) datasets and one NSE dataset to get your hands dirty in processing real world datasets and gleaning basic insights from them.

Completing the above will set you up for learning higher order computing skills such as Web Development, Data Science, AI, Generative AI etc.

Our focus throughout will be to make every concept easy to understand, intuitive to ‘stick’ and develop skills which are real world relevant.

Check out our first 3 full classes here:
Session 1- https://youtu.be/DS6uUi5QaSY
Session 2- https://youtu.be/N0Xio5sgPc4
Session 3- https://youtu.be/XYEc2z7Dcs0
Note:
Coding is “only” learnt through self-practice. We highly encourage you to run each and every line of code shown in the class, yourself – try its variations, encounter ‘errors’ and try to debug yourself as much as you can (we are of course there if you get stuck). Practice will build neural paths in your brain that will make coding ‘intuitive’.

We use the term ‘coding’ primarily as a reference to algorithmic thinking’, which entails logical process based approach to problem solving where code is only automating the solution.

Format

Pre-start instructions on downloading Python environment and starting a Jupyter Notebook
11 sessions, each a 2 hour self-explanatory recorded class room session
11 detailed notes files, each carrying all the codes from the sessions

Detailed curriculum below

Option 1
Pre-start instructions on downloading Python environment and starting a Jupyter Notebook
11 sessions, each a 2 hour self-explanatory recorded class room session
11 detailed notes files, each carrying all the codes from the sessions

4 hours live interactive sessions to address queries (1 hours every Saturday or Sunday in the morning)
(Recordings of these interactive sessions will be available to you)

Fee: INR 6999

Option 2
Pre-start instructions on downloading Python environment and starting a Jupyter Notebook
11 sessions, each a 2 hour self-explanatory recorded class room session
11 detailed notes files, each carrying all the codes from the sessions

Send us your queries of the week by Thursday and we will revert with a video recording (to you can refer to it as many times as needed) explaining the solution, by Sunday

Fee: INR 3999

Query support will be for 30 days from enrolling; however, class recordings will be available for 2 months

Enrollment

Please send us an email @ [email protected] with following details –
1. preferred learning format
2. name of learner
3. learner profile (student-school/college student/working professional/others)
4. Email for formal communication
we will revert with simple instructions to get you started

Consultation

If you would like to consult us over a voice call to understand about curriculum and/or generally to understand the scope of Python, please email us at [email protected]

Consultation fee: INR 1500 for 30 min

Curriculum

Session 1
Python Operators, Variables, Data Types
Session 2
Lists, Tuples, Dictionaries
Session 3
Dictionary, Data Type Conversions, if/else, Loops, Python Functions,
Exercise - Generate synthetic data using ‘for loops’ and ‘dictionary’ and perform data sorting
Session 4
Recursive functions, nested dictionaries, local and global variables, lambda function, map() and reduce ()
Session 5
Python functions, models, date and time, input function, Assertions and Exceptions, start of NumPy
Session 6 & 7
NumPy (numerical python)
Session 8 & 9
Pandas
Exercise1 - Data Analytics on Hollywood dataset from Kaggle (find the most profitable movie genres and most bankable actors)
Exercise2 - Data pre-processing and data exploration on NSE stock data (clean the data, filter prices of stock by stock name, sector name, plot prices and moving averages and observe price trend vis-a vis moving averages)
Session 10
Pandas, Class and Objects
Session 11
Class and Objects, Data Visualization using Matplotlib

Final Project
Data Processing, Visualization and exploratory analytics on Cardiovascular disease prediction dataset from Kaggle

#python #datascience #generativeai