Data Science Course Curriculum

Syllabus

Price $5400

Data Science Immersive (Morning) Mon 9 am - 12pm
Wed 9 am - 12pm
Fri 9 am - 12 pm
12/10/2018 & 12/24/2018 6/10/2019 $5,400
Data Science Part Time (working professionals) Mon 6 pm - 9 pm
Thurs 6 pm - 9 pm
Sun 3 pm - 6 pm
12/10/2018 & 12/24/2018 6/10/2019 $5,400
Data Science Immersive (Noon) Mon 12 pm - 3 pm
Wed 12 pm - 3pm
Fri 12 pm - 3 pm
12/10/2018 & 12/24/2018 6/10/2019 $5,400
Python for Beginners Sat 2:30 pm - 6 pm
Sun 2:30 - 6 pm
Every First Sunday - Ask
Contact: info@bainyc.com (Syed (347) 639-1745) Monthly payment plan & scholarship for underrepresented
Syllabus for Part time version
1 Week 0: PRE-WORK TOPICS
2 Tools required for Data Science - Cloud, Python, Database
3 Intro to Python
4 Functional and Object Oriented Python
5 STATISTICAL FUNDAMENTALS
6 Pandas Data Analytics
7 Data Cleaning Wrangling
8 REGRESSION AND AND EXPLORATORY USING PANDAS
9 Graphs and Charts using Matplot, Sea Born, Pyplot
10 Dimensionality Reduction And Time Series Data
11 Classification and Logistic Regression
12 Natural Language Processing
13 Decision Trees,Random Forests, Naive Bayes
14 Neural Network & Artificial Intelligence
15 Deep Learning on Tensorflow and Keras
16 SQL and Databases
17 Data Engineering - Hadoop Developer and Admin, MongoDB
18 Spark, Scala, Hive, Hbase
19 Django / Flask
20 FLEXIBLE CLASS SESSION / Project / Interview Prep
21 FLEXIBLE CLASS SESSION / Project / Interview Prep
22 FLEXIBLE CLASS SESSION / Project / Interview Prep
23 Final Presentations
24 Interview Prep

INTRO DO DATA SCIENCE OVERVIEW AND THE FRAMEWORK
AUDIENCE: DATA ANALYSTS OR BUSINESS INTELLIGENCE ANALYSTS
PRE-WORK TOPICS
Introduction to Python
Tools required for Data Science
RESEARCH DESIGN AND EXPLORATORY DATA ANALYSIS
RESEARCH DESIGN AND PYTHON PANDAS / DATA WRANGLING TERMS AND CONCEPTS
STATISTICAL FUNDAMENTALS
REGRESSION AND AND EXPLORATORY USING PANDAS
FOUNDATION OF DATA MODELING
EVALUATING MODEL FIT
Classification and Logistic Regression
INTRODUCTION TO CLASSIFICATION
LOGISTIC REGRESSION I
COMMUNICATING LOGISTIC REGRESSION RESULTS
Decision Trees,Random Forests and Natural Language Processing
Dimensionality Reduction And Time Series Data
DIMENSIONALITY REDUCTION
CREATE MODELS WITH TIME SERIES DATA
Data Engineering
Database Technologies
Big Data Technologies
Final Project Presentations

 

Python Classes for Begineers

Python 101 Class NYC

Python 101: 3 hours
Group size: 3-4

Python 101 Course Outline

Sunday: Python Part 1 & Part 2

9 am to 4 pm

Mon: Data Science 101

9 am - 8 pm

Tues: Machine Learning 101

1:30 - 3:30 pm

Wed: Advanced Pandas Data Science

9 am - 5 pm

Thu: Machine Learning Part 2

2 pm - 8 pm

Fri: Machine Learning Project

9 am - 4 pm

Sat: Fine Tuning, PPT and Github

9 am - 6 pm