Saturday, July 21, 2018

Python Data Science 101 Bootcamp (Beginners and Non Programmers) 6 hrs PAID $65 Python Data Science Machine Learning Bootcamp NYC

 New York Python SQL Bootcamp Coding Classes (Affordable & Cost-effective Machine Learning). Best Free classes in NYC. SQL 101 & Python 101 Classes. Big Data Science Classes for beginners interested in Analytics & Data Science. Weekend part time and full time classes in Manhattan & Queens. 1 on 1 Tutoring also available. Free weekend 2hrs class.

https://www.meetup.com/New-York-Python-SQL-Bootcamp-Data-Science-Analytics/events/251782354/

Python Data Science Machine Learning Bootcamp NYC

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.

Check out our PPT and Jupyter Notebook 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.

Part 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

Joshi