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Python 1 Week Bootcamp to build Portfolio [Paid $499] Batch Size Max 2
October 15 @ 8:00 am - October 19 @ 3:00 pm
FREE RETAKESPython Immersive $499 (Fee Adjusted from 2 Day bootcamp if attended)35 hours in total, 5 sessions/days of 7 hours eachMonday to Friday 8 am to 3 pmThe course is developed for non programmers and non stat audience.It consist of games, graphics, and examples to sensitize you to the terms used in Data Science.Day 1 / 2 (This course is prerequisite for Part 2)Notes for 1st Session:https://notebooks.azure.com/shivgan3/libraries/PythonClassesNYCBootcamphttps://docs.google.com/presentation/d/1LmBC6uq2iZPDSnqjdaZqILkDJjl4SB-97ARgPFEejHE/edit?usp=sharingGroup size is max 3.Topics: Introduction to Python Foundations of programming:Python built-in Data types Concept of mutability and theory of different Data structures Control flow statements: If, Elif and Else Definite and Indefinite loops: For and While loops Writing user-defined functions in Python Classes in Python Read and write Text and CSV files with python List comprehensions and Lambda. Classes and inheritance.Print Hello World Azure Notebooks & Anaconda Book and Content Functions (Arguments and Return) Loops (For While) If else List/DictionaryNested Loops with if else List/Dictionary (JSON) Class Lambda Functions List ComprehensionFile Handling Web Scraping Exception handling SQLite PythonCapstone Project for Github PortfolioMatplotlib Numpy Pandas Scipy Python Lambdas Python Regular Expressions Collection of powerful, open-source, tools needed to analyze data and to conduct data science.Working with jupyter anaconda notebooks pandas numpy matplotlib git and many other tools.Data Loading, Storage, and File FormatsData Cleaning and PreparationData Wrangling: Join, Combine, and ReshapePlotting and VisualizationData Aggregation and Group OperationsTime SeriesReference Github:https://github.com/BrambleXu/Automate-the-Boring-Stuff-with-Python-Solutionshttps://github.com/lukaszsi/Automate-the-Boring-Stuff—practical-taskshttps://github.com/ubarredo/LearnPythonTheHardWayhttps://github.com/wesm/pydata-bookDay 2/2PPT: https://docs.google.com/presentation/d/1HrmkW6d53I6YETWS5pDDhE6E3OXTlDljcHyjARLdLIE/edit?usp=sharinghttps://notebooks.azure.com/shivgan3/libraries/MachineLearningAIhttps://notebooks.azure.com/shivgan3/libraries/PythonMLPart2Python Data AnalyticsWe’ll cover the machine learning and data mining techniques are used for in a simple example in Python.Regression analysis K-Means Clustering Principal Component Analysis Train/Test and cross validation Bayesian Methods Decision Trees and Random Forests Multivariate Regression Multi-Level Models Support Vector Machines K-Nearest Neighbor Bias/Variance Tradeoff Ensemble LearningReference Github:https://github.com/wesm/pydata-bookhttps://github.com/jakevdp/PythonDataScienceHandbook(Portfolio Building for your project)Day 3Select your project, download data, clean wrangle and massage your data and make it ready for anaysisDay4Run Machine Learning Models and select the best modelTweak Model parametersDay 5Fine tune and publish your portfolio#Instructor:Shivgan [email protected] 356 5046https://github.com/shivgan3https://www.linkedin.com/in/shivganjoshi/https://notebooks.azure.com/shivgan3/libraries** Payment Policy: We only accept payment at door and before the class. We accept payment through event leap, cash, Venmo & Paypal(+5). **