Course Summary: Data Analytics
                Our Data Analytics evening course is an 6 week course, and it does not require any prior programming experience.
                Data Analytics is the art of understanding and processing data with the goal of drawing conclusions
                    about that data.
                    In the "old days" data was limited, so it is easy to process data on books using hand calculations.
                    But as the data sets
                    becomes large we need sophisticated tools to process them.
                    
                    Data Analysts mine huge data sets using complex software such as UNIX, Excel, SQL and Python. In
                    this course you will not only learn how to master the necessary skills to process the data sets using the aforementioned tools but
                    also develop an intuition to derive conclusions about given problem.
                    
                    Data Analytics is a mix of Computer Science (C), Statistics (S), & Management Skills (M). 
                
                    
                        
                        Course Details: Evening course Data Analytics
                         Week 1 : Excel Essentials
                        
                            - C: Introduction to Excel Data Analytics
- C: Excel Shortcuts
- C: Data Munging in Excel
- C: Pivot Tables and Lookup tables
- C: Getting data in excel from various sources (SQL databases, websites, etc ... )
- C: Story telling with data in excel
Week 2 : Unix for Data Analytics
                            - C: Getting started with UNIX
- C: Complex Data Manipulations using UNIX
- C: Exploring Data using UNIX
- C: Bash Scripting
Week 3 : SQL for Data Analytics
                            - C: Introduction to SQL
- C: Data Munging with SQL
- C: Data Aggregation
- C: Replicate Excel Pivot tables in pure SQL
Week 4 : Core Python
                            - C: Introduction to Python
- C: Data Exploration
- C: Working with Pandas for Data Analysis
- C: Visualize data using Python 
Week 5 & 6: Projects, putting it all together
                            - M: Story telling with data
- M: Effective presentation skills with data and visualizations
- M: Best practices for data management and analytics
- C: Sample Projects: Stock Portfolio Returns Analysis
- C: Sample Projects: Market Segmentation Analysis 
Data Analytics: Learning Objectives
                            - No prior programming experience required! 
- Learn to apply strategies to solve data-driven problems   
- Enhance analytical thinking
- Tools used : Excel, UNIX, MySQL, Python, Pandas module
- Most Important: Learn to converse with data and keep it simple. Use common sense!
 Next Steps:
                        
                     
                 
                
                Campus
                
                Next Cohort
                        
                            -  January 9th, 2017 - February 15th, 2017
                            
 Monday and Wednesday:  6:30 PM to 9:30 PM
Tuition
                
                Financing
                Financing Options available with: 
                Pave