The 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.
Notes for 1st Session: https://notebooks.azure.com/shivgan3/libraries/PythonClassesNYCBootcamp
https://docs.google.com/presentation/d/1LmBC6uq2iZPDSnqjdaZqILkDJjl4SB-97ARgPFEejHE/edit?usp=sharing Group size is 5.
This course is prerequisite for Part 2. Thanks to Math matter for providing us the venue.
Day 1 / 2 Two day intensive boot camp for Python Data Science Enthusiast. 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 How to start using Python Parsing information with Python Practice Python to solve the real-world tasks Skills that you will GAIN while working on the course are: Python Programming Language Statistical Hypothesis Testing IPython Hypothesis-testing Matplotlib Numpy Pandas Scipy Python Lambdas Python Regular Expressions Collection of powerful, open-source, tools needed to analyze data and to conduct data science.
Specifically, you’ll learn how to use: python jupyter anaconda notebooks pandas numpy matplotlib git and many other tools. We’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 Reinforcement Learning Collaborative Filtering K-Nearest Neighbor Bias/Variance Tradeoff Ensemble Learning Experimental Design and A/B Tests
#Instructor:
Joshi
Cell 929 346 5046
Prepay