Craiglist Adds: Data Science Bootcamp

Financial Modeling Tutor $25/hr (Midtown)

I am a former investment fund analyst and experienced in investment banking. 

Offering lessongs on excel, especially build models for companies.

Very affordable rate of $25, and you will be given all the skills needed to land a job at a hedge fund, investment bank, or private equity firm.

Valuation Methods for Companies, putting together models, write-ups, and presentations.

This is a very limited service and is temporarily offered for this month while I am vacation and interested to share what I learned.

Take advantage while you can, hours are limited, availability also at 6 pm - just after your office.

Feel free to contact me if you are interested in learning how to be an finance/excel expert! Thank you!    

Google Sheets and App Script (JavaScript) tutor $25/hr (Manhattan)

Hi,

I am a tutor for Google App script (Java script) used for automation in Google sheets. If your company is using google sheet learning automation will help you to progress. Also, important for business students.
Charge $25/hour.
Location: All in NYC area.
Please get in touch

.    

GRE / GMAT Quant / Quantitative/ Math Tutor $25/hr

GRE / GMAT Quant Tutor

Experience in tutoring, videos online and good references.
Price $25 per hour
5 years of exp in quantitative GRE GMAT tutoring
From the author of FreeGREGMATClass dot com
Check out the youtube videos contributed by students and tutors for FGGC
First session of 30 minutes is free.   

Quantitative Math Excel VBA $25/hr (New York)

Tutoring Data Science has been my hobby and recreational activity. Many tutoring projects are volunteering and networking oriented (getting new insight). I do it so that I can revise what I do at school and at work. I am an Electrical Engineering graduate, GAARP-FRM certified, PG Dip in Fin analysis and Risk Management, cleared CFA L1, International - MBA (15-16).

I have extensive teaching experience with students of various profiles and backgrounds where I have learned and enhanced my skills and also helped learners. I am also an extremely friendly person. I have taken many online classes as tutor on qcfinance.in

QcFinance.in has tutors available for meetups (mix of onsite at home & online through Wiziq/Skype/Adobe-connect & custom videos support emailed to you for your doubts on holidays)

Subject areas teach includes: Quantitative Methods for GRE / SAT / GMAT, CFA L1, FRM L1, MATLAB/R/SPSS for Quant, Excel-VBA Programming. Quantitiative and Analytics Excel programming & VBA programming.

Sub topics:

Basics of Excel: Vlookups, Hlookups, Index Match, Dependents, Data tables (1 way and 2 ways), Pivots, Charting, Filters, SQL integration, VBA coding, Address and indirect, Offset, Array functions, etc.

Applications: Regression, Histograms, Monte carlo simulation, rank correlation, dashboards, more.
Automation using VBA: Loops (for, do while, case), Recorder, Arrays and Matrices, if else, indexing, etc.

Website: www.qcfinance.in

Playlist of sample quant videos: https://www.youtube.com/playlist?list=PL_-KSXJS5pxOiLjAoe5uAHPAsv-UhIM7i

Keywords: Quant Trainer, Tutor, Trainer, Teacher, Home tuition, GRE, GMAT, Quant, Programming, CFA Level 1, FRM Part 1, Mathematics Tutor, Maths, Onsite.

Keywords: Trainer, Tutor, Home tuition, Excel, VBA, Onsite, trainer, help assignment, video solutions, In Person, 1 on 1, Home Tutor. 

Office Automation on Excel VBA Python SQL R (new york)

We provide official automation services on Excel VBA Python SQL R. 

Automation is the next biggest revolution, legacy methods if not replaced by automation will reduce the productivity of the firm which might even lead to extinction.

Our can reduce a lot of manual work and use lot of Excel Analytics features, our clients have reduced work by upto 50-70% which helped me focus on their product and other value addition to their core business.

Get more hours from your employees and more robust analytical framework!

Please contact me for more details about various processes that we can automate.    

Statistics, Data Science, Machine Learning, Statistical Computing, R   

Tutoring for statistics, machine learning, and data science. The focus includes statistical theory as well as its application, building models. That includes the following: 

•Theory Courses: Probability, Statistical Inference, Bayesian Statistics, Decision Theory, Point Estimation, High-Dimensional Inference, Time Series, and other MS/Ph.D. courses

•Machine Learning: Ridge Regression, LASSO, Basis Pursuit, Supervised/Unsupervised Learning, Neural Network, Statistical Learning Theory 

•Social Science: Causal Inference, Hierarchical Model, Multiple Imputation, Matching

•Statistical computing: R programming, Matlab, STATA, Python, Java, C

Analytics course New York

PROJECTS
FINAL PROJECT For the Analytics final project, you will collect, clean and
analyze a data set to solve a real world problem. From this
data, you will segment the data set and perform analysis.
Following your analysis, you will create both a dashboard and
presentation.
In order for your project to be considered a success, you will
complete the following steps
‣ Identify a problem
‣ Obtain the data
‣ Understand the data
‣ Prepare, clean and format the data
‣ Analyze the data
‣ Create a dashboard to display insights both numerically and
graphically.
‣ Present high level insights and the resulting actions to key
stakeholders.
As you complete elements of your final project, you will be
required to present materials and receive feedback from your
instructional team and classmates as well industry experts.
Our instructors are on hand to validate the feasibility and
manage the scope of your project.
6
Data Analytics
Units

UNITS
UNIT 1: DATA IN EXCEL ‣ The Value of Data Lesson 1
‣ Prepare Data in Excel Lesson 2
‣ Clean Data in Excel Lesson 3
‣ Dynamic Data Referencing Lesson 4
‣ Dynamic Data Aggregation Lesson 5
‣ Conditional Formatting and Aggregation Lesson 6
‣ The Value of Databases Lesson 7
‣ Query Large Databases Lesson 8
‣ Data Aggregation in SQL Lesson 9
‣ More Data Aggregation in SQL Lesson 10
‣ Efficient and Dynamic Queries Lesson 11
‣ Present Analysis Results Lesson 12
‣ Statistics to Validate Analysis Lesson 13
‣ Predictive Analysis Lesson 14
‣ Dashboard Design Lesson 15
‣ Track Metrics with Dashboards Lesson 16
‣ Effective Presentations with Data Lesson 17
‣ Flexible Session Lesson 18
‣ Flexible Session Lesson 19
‣ Final Project Presentation Lesson 20
UNIT 2: DATA IN SQL

UNIT 2: COMMUNICATION AND
DASHBOARD DESIGN
1 THE VALUE OF DATA
‣ Explain the value of data.
‣ Describe the analytics workflow
‣ Use mean, median, mode to describe data and find outliers
2 PREPARE DATA IN EXCEL
‣ Describe best practices in data cleaning and collection to
ensure the best results from data analysis
‣ Use complex nested logical functions [IF, OR, and AND] to
further manipulate data sets
‣ Manipulate data formats to gain insights on how to analyze
data
3 CLEAN DATA IN EXCEL
‣ Clean a large messy datasets by removing duplicate rows
and performing text manipulations
‣ Transform and rearrange columns and rows to structure
data for analysis
‣ Manipulate data formats to gain insights on how to analyze
data
4 DYNAMIC DATA REFERENCING
‣ Use data functions [VLOOKUP and HLOOKUP] to
manipulate data sets
‣ Use data functions [INDEX and MATCH] to look up values
in other tables
‣ Reconcile data values by joining and matching
5 DYNAMIC DATA AGGREGATION
‣ Summarize data using the pivot tables
‣ Use excel aggregation commands [‘Min’, ‘Max’, ‘Sum’,
‘Average’, ‘Count’, ‘Frequency’ to accomplish “count
distinct” ] and their conditional variants [‘COUNTIF’,
‘COUNTUNIQUE’, ‘COUNTA’, ‘COUNTIFS’,
‘COUNTBLANKS’] to summarize data sets
6 CONDITIONAL FORMATTING AND AGGREGATION
‣ Derive insights from data by highlight cells based on
conditionals
‣ Describe color theory and how it applies to data visualization
7
Data Analytics
Units Continued

DATA IN EXCEL 1
8
Data Analytics
Units Continued
GA.CO/AN
7 THE VALUE OF DATABASES AND SQL
‣ Use database schema to design appropriate queries
‣ Explain differences between relational databases (tabular
data storage) and document-based databases(key-value
pairs)
‣ Collect data using standard sql commands [Select, From,
Create, Update, Delete, Truncate, Drop]
8 QUERY LARGE DATABASES
‣ - Use advanced SQL commands [where, groupby, having,
orderby, limit] to filter data
‣ - Use joins to create relationships between tables to obtain
data
‣ - Use SQL boolean operators [AND and OR] and SQL
conditional operators [=,!=,>,<,IN and BETWEEN] to
obtain filtered data
9 DATA AGGREGATION IN SQL
‣ U- Create relationships between tables and data points
including has_many and many_to_many with join tables
using Joins [‘full’, and ‘union’]
‣ - Use sql conditional operators [=,!=,>,<,IN and
BETWEEN] and Null functions[‘is Null’, ‘ is not Null’ and
‘NVL’ ] to create boolean statements
‣ - Use sql mathematical functions [ABS, SIGN, MOD,
FLOOR, CEILING, ROUND, SQRT] to clean data
10 MORE DATA AGGREGATION IN SQL
‣ - Use aggregation commands [‘Min’, ‘Max’, ‘Sum’, ‘Average’,
‘Count’, ‘Count Distinct’] to summarize data sets
‣ - Use aggregation methods to determine trends from data
11 EFFICIENT AND DYNAMIC QUERIES
‣ Use CASE statements to structure data and create new
attributes
‣ - Use "WITH AS (" to combine subqueries into one query
‣ - Present analysis results and describe stakeholder
implications and insights
DATA IN SQL 2
9
Data Analytics
Units Continued

12 PRESENT ANALYSIS RESULTS
‣ Provide appropriate context of dataset
‣ Appropriately describe analysis techniques
‣ Present and describe stakeholder implications and insights
13 STATISTICS TO VALIDATE ANALYSIS
‣ Describe the value of descriptive and summary statistics in
understanding a dataset
‣ Create basic statistical measures to better understand the
range, average, and variance within a dataset
‣ Present the most salient statistics in order to provide
context to your audience
‣ Explain the importance of segmentation
14 PREDICTIVE ANALYSIS
‣ Describe the value of inferential statistics and predictive
analysis
‣ Review linear regression and Ordinary Least Squares (OLS)
‣ Use sample data to make predictions about a larger
population
15 DASHBOARD DESIGN
‣ Use scatter plots and bar graphs to visualize data
‣ Apply the best practices to build a dashboard
‣ Demonstrate good visual design without overloading their
dashboard with complexity
16 TRACK METRICS WITH DASHBOARDS
‣ Use bubble graphs to visualize data
‣ Apply the best practices to build a dashboard
‣ Contextualize data analysis by creating Tableau dashboards
[includes charts + conditional formatting] with supporting
information specific to the dataset
17 EFFECTIVE PRESENTATIONS WITH DATA
‣ Display geocoded information in Tableau
‣ Provide real-world context for basis of analysis
‣ Provide localized context for implications of findings
‣ Deliver short, effective presentations
DATA ANALYSIS 2 (CONTINUED)
DATA COMMUNICATION 3
10
Data Analytics
Units Continued

18 FLEXIBLE SESSION
‣ Focus on a topic selected by the instructor/class in order to
provide deeper insight into a specific area of data analysis
19 FLEXIBLE SESSION
‣ Focus on a topic selected by the instructor/class in order to
provide deeper insight into a specific area of data analysis
20 FINAL PROJECT PRESENTATION
‣ Present final project presentation to class

SQL:Fundamentals of Querying Course New York Manhattan

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. Small group courses (2-3 attendees), free takes and 1 on 1 : Python 101, Python Data Science Immersive Python for Data Analytics. VBA Macros Immersive. SQL 1 day Class.Project and Portfolio Oriented on weekends and also free evening classes in NYC. Upload your portfolio to get better job. Best Python Class in NYC. FREE RETAKES.

SQL:Fundamentals of Querying Course New York Manhattan NYC


Introduction to Practical SQL for Data Analytics (3 hours) Duration: 1 day(s)
Prerequisite: Basic Excel

What will  you achieve from this course:
Create a DB design for your work data you see in excel at your office
Understand Data Wrangling using Group, Joins and PIVOT to get data in the format you need for any data that comes to you adding new insight
Get Excel equivalent functions for SQL commands
Understand the terms in Data Analytics that remain university to all languages (Python / R / SQL)
Project - Convert a simple Excel data in SQL and learn how scripting would automate manual task


Introduction to need of SQL and Design Aspects

Why do we need SQL? What is wrong with excel?For example: if we create the information of people attending the classes - what is wrong with that?
How will SQL give us some better way of handling it?
Top 5 problems in Excel 
Can I and should I move all my data of work from excel to SQL? How would I do that?

Can I link Excel with SQL?


 Project: Table of people attending the class



Getting Hands on with SQL and Outline

Executing a Simple Query
Connect to the SQL Database - Can you control access to users for specific sheets in excel? what about SQL?
Query a Adventure Work Database / OGCBooks
Save a Query and Modify a Query
Execute a Saved Query


Why do we need condition - what is the Excel equivalent?
Performing a Conditional Search
Search Using a Simple Condition (Filtering)
Compare Column Values
Search Using Multiple Conditions
Search for a Range of Values and Null Values
Retrieve Data Based on Patterns

SQL Functions -
Pre build and predefined Functions in SQL
Working with Functions
Perform Date Calculations
Calculate Data Using Aggregate Functions
Manipulate String Values Organizing Data

Sort Data
Rank Data

Data Wrangling and Data Analytics
Group Data (the most important concept of the class)
Filter Grouped Data
Summarize Grouped Data
Use PIVOT and UNPIVOT Operators (Broad concept that goes to R, Python, SAS, Tablue everywhere)

Retrieving Data from Tables
Combine Results of Two Queries
Compare the Results of Two Queries
Retrieve Data by Joining Tables
Check for Unmatched Records
Retrieve Information from a Single Table Using Joins

Presenting and Making sense of Query Results
Save the Query Result
Generate an XML Report

Appendix A:
The OGCBooks Database
Adventure work Database provided by MS.
 
After completing this course, students will know how to:
Understand why SQL is needed as a solution to limitation of excel
Connect to the SQL Server database and execute a simple query.
Include a search condition in a simple query.
Use various functions to perform calculations on data.
Organize data obtained from a query before it is displayed on-screen.
Retrieve data from tables.
Format an output, save a result, and generate a report.

R Analytics data science

http://nycdatascience.com/data-science-bootcamp/

Excel VBA Class in Manahttan

Below are the list of classes I found in Manhattan.


Active - First
http://vbaclass.com/excel-classes/vba-classes/
421 7th Ave, New York, NY 10001
excel-training-nyc.com
Phone: 212-537-6125
Address: 421 7th Avenue, 4th Floor

Last
Sam - not small but not that big also
1723 E 12th St, Brooklyn, NY 11229
samconsulting.com


Moribound 2nd:
http://www.exceltrainingnyc.com/index.html
545 8th Ave
Suite 1530
New York, NY 10018
Phone: 212-564-2351

Quant /Math Tutoring in NYC areas close to Ozone Queens

To be checked:
http://www.flexprep.org/ - Closest

http://www.parkslopetutoring.org/ - down in Brooklyn
http://www.ridgewoodtutors.com/contact/ - Closest
http://pinnacleprep.com/ - Close to Iskon
https://www.ontutoring.com/ -  Close

https://www.kumon.com/KEW-GARDENS

http://alohamindmath.com/

Data Science Programs in New York

Python for Data Science & Machine learning

Course by QcFinance.in

Skills that you will GAIN

• Python Programming Language
• Statistical Hypothesis Testing
• IPython
• Hypothesis-testing
• NetworkX
• Matplotlib
• Numpy
• Pandas
• Scipy
• Python Lambdas
• Python Regular Expressions

Python Basics

An introduction to the basic concepts of Python. Learn how to use Python both interactively and through a script. Create your first variables and acquaint yourself with Python's basic data types.

Learn to store, access and manipulate data in lists: the first step towards efficiently working with huge amounts of data.

Functions and Packages

To leverage the code that brilliant Python developers have written, you'll learn about using functions, methods and packages. This will help you to reduce the amount of code you need to solve challenging problems!

NumPy

NumPy is a Python package to efficiently do data science. Learn to work with the NumPy array, a faster and more powerful alternative to the list, and take your first steps in data exploration.

Course Syllabus

Section 1: Python Basics

Take your first steps in the world of Python. Discover the different data types and create your first variable.

Section 2: Python Lists

Get the know the first way to store many different data points under a single name. Create, subset and manipulate Lists in all sorts of ways.

Section 3: Functions and Packages & Control flow and Pandas

Learn how to get the most out of other people's efforts by importing Python packages and calling functions.

Write conditional constructs to tweak the execution of your scripts and get to know the Pandas DataFrame: the key data structure for Data Science in Python.

Section 4: Numpy and Matplotlib

Write superfast code with Numerical Python, a package to efficiently store and do calculations with huge amounts of data.

Create different types of visualizations depending on the message you want to convey. Learn how to build complex and customized plots based on real data.

Collection of powerful, open-source, tools needed to analyze data and to conduct data science. Specifically, you’ll learn how to use:

• python
• jupyter notebooks
• pandas
• numpy
• matplotlib
• git
• and many other tools.

We'll cover the machine learning and data mining techniques real employers are looking for, including:

• 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
• Term Frequency / Inverse Document Frequency
• Experimental Design and A/B Tests

Statistics and Probability Refresher, and Python

• Bayes' Theorem
• Predictive Models
• Linear Regression
• Polynomial Regression
• Multivariate Regression, and Predicting Car Prices
• Multi-Level Models
• Machine Learning with Python
• Supervised vs. Unsupervised Learning, and Train/Test
• Using Train/Test to Prevent Overfitting a Polynomial Regression
• Bayesian Methods: Concepts
• Implementing a Spam Classifier with Naive Bayes
• K-Means Clustering
• Clustering people based on income and age
• Measuring Entropy
• Install GraphViz
• Decision Trees: Concepts
• Decision Trees: Predicting Hiring Decisions
• Ensemble Learning
• Support Vector Machines (SVM) Overview
• Using SVM to cluster people using scikit-learn
• User-Based Collaborative Filtering
• Item-Based Collaborative Filtering
• Finding Movie Similarities
• Improving the Results of Movie Similarities
• Making Movie Recommendations to People
• Improve the recommender's results
• More Data Mining and Machine Learning Techniques
• K-Nearest-Neighbors: Concepts
• Using KNN to predict a rating for a movie
• Dimensionality Reduction; Principal Component Analysis
• PCA Example with the Iris data set
• Data Warehousing Overview: ETL and ELT
• Reinforcement Learning
• Dealing with Real-World Data
• Bias/Variance Tradeoff
• K-Fold Cross-Validation to avoid overfitting
• Data Cleaning and Normalization
• Cleaning web log data
• Normalizing numerical data
• Detecting outliers
• –Apache Spark: Machine Learning on Big Data
• Installing Spark - Part
• Spark Introduction
• Spark and the Resilient Distributed Dataset (RDD)
• Introducing MLLib
• Decision Trees in Spark
• K-Means Clustering in Spark
• TF / IDF
• Searching Wikipedia with Spark
• Using the Spark 2.0 DataFrame API for MLLib
• Experimental Design
• A/B Testing Concepts
• T-Tests and P-Values
• Hands-on With T-Tests
• Determining How Long to Run an Experiment
• A/B Test Gotchas

Please email info@qcfinance.in to know more information.

  

Some links from online search:

www.skilledup [dot] com/articles/list-data-science-bootcamps

Generalassemb[dot]ly/education/data-science

Some general Videos That are suggested:
https://www.youtube.com/playlist?list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y

Data Analytics courses in NY

COURSE DESCRIPTION:

This unique comprehensive course provides solid knowledge in Data Analysis and Statistical Software. Through a combination of lectures and exercises, students will learn the key techniques and approaches necessary to be an effective Data Analyst.
Students will learn fundamentals of Data Analysis with Python programming, advanced Excel techniques and VBA macros, basics of SQL Server Databases In the end of the course students will polish their knowledge practicing Data Analysis projects.

COURSE CONTENT:

1. Statistics for Business. Overview – students will review basic concepts and terminology in Statistics, including: Mean, Mode, Range, Standard Deviation, Normal Distribution, T-Distribution, Hypothesis Testing, Chi Square Test, A-B Testing etc.
 
2. Python Programming Fundamentals – the module includes following topics: Basic Data Types (Basic Data Types, Variables, Operators, Functions and Modules), Compound Data Types (Lists, Strings,  Sets, Dictionaries), Flow control (Conditional expressions, Loops, Iterators), Working with files, Working with functions, OOP Concepts, Benefits of Standard Library.

3. Data Analysis and Visualization with Python – module provides solid fundamentals of Data Analysis and Data Visualization using Python Libraries: Numpy, Pandas and Seaborn. Students will learn Machine Learning (Linear Regression, Logic Regression etc) and Data Visualization with Histograms, Kernel Density Plots, Box and Violin Plots, Clustered Matrices, Regression Plots etc.

4. Advanced Excel Techniques – in this module students will learn Excel advanced techniques, including Math Functions, Logical Functions, Statistical Functions, Lookup, Sort/Filter Data, Pivot Tables and Pivot Charts, Data Analysis Tools etc.

5. VBA Programming Fundamentals – this module provides VBA Programming fundamentals, including VBA Sub Procedures, VBA Function Procedures, Excel Objects, and using Macros. VBA is simple but powerful scripting language that will help to analyze data, work with objects and develop automated procedures.

6. Microsoft Access. Overview – this module student reviews fundamental functions of Microsoft Access, such as Tables and Datasheets, Lookups, Forms, Reporting etc.

7. Introduction to SQL Server Databases – this module provides students with the understanding of database concepts and the essentials of relational database with the SQL language. Through a series of hands-on activities students will learn data selection and manipulation using multi-vendor compliant SQL syntax and writing simple queries. The module includses: data types, table structure, essential SQL commands, retrieving data, queries, group functions, data manipulation, control transactions etc.

8. Data Visualization with R – in this module students learn fundamental, intermediate and some advanced techniques for Data Visualization and Business Intelligence. The module starts with the following topics: using the R interface/paradigm to create data visualizations, creating basic calculations (arithmetic, custom aggregations/ratios, date math, and quick table calculations), building Dashboards to share visualizations. After this module students will know how to build some advanced chart types and visualization, complex calculations to manipulate data, use statistical techniques to analyze data, implement advanced geographic mapping techniques and visualizations of non-geographic data, prep data for analysis, combine data sources using data blending.

9. Data Analysis Projects Workshop – at the end of the course students will polish their knowledge practicing Data Analysis and Data Visualization with Excel, Access, Python and R.

180 instructor-led class hours, plus labs

Prerequisites:
Basics of Statistics and Excel. Related education or work experience is a plus.


CREATING RECORD MACROS
Recording a Macro
Running a Macro
Running a Macro from the Macros Dialog Box
Creating a Short-cut key to run a macro
Running a Macro with a Shortcut key
Assigning a Macro to a Menu or Toolbar
Editing a Macro with Visual Basic
VISUAL BASIC EDITOR
Objects
Methods
Properties
Programming Tools
The Menu Bar
THE PROJECT EXPLORER
Using the Project Explorer
USING CONSTANTS
Excel Constants
Variable Constants
EXCEL OBJECTS
Objects, Properties and Methods
Getting & Setting Properties
Calling Methods
Passing Arguments
Singular Objects & Collections of Objects
USING VISUAL BASIC FUNCTIONS
InputBox Function
MsgBox Function
Using a Set Statement
BUILDING FORMULAR CONTROL STRUCTURES
If Then Janision Structures
Logical Operators
Select Case Janision Structures
Case Else
Comparison Operators with Select Case Structure
For Loops
Do Loops
While...Wend Statement
RUNNING CODE
Run mode and Design mode
Running Code from the development environment
Running Code from the host application
THE PROPERTIES WINDOW
Changing a Property
VARIABLES
Dimensioning a variable
Using variables in routines
Object Variables
USERFORMS
Designing & Creating Forms
Working with Controls
Creating Custom Dialog Boxes
Userform Properties Methods & Events
ADVANCED VBA PROGRAMMING TECHNIQUES
Developing Excel Utilities with VBA
Error Handling
Using In-Built Excel Features in VBA
Working with Pivot Tables
Working with Charts
Understanding Excel's Events
Interacting with Other Applications
Creating and Using Add-Ins
DEVELOPING APPLICATIONS
Working with the Ribbon
Working with Shortcut Menus
Providing Help for Your Applications
Developing User Oriented Applications
EVENT HANDLING
VBA Editing & Debugging
Auto Macros
Error Handling

VBA Consultancy in NYC

Importing csv:
http://www.homeandlearn.org/open_a_text_file_in_vba.html

Charts:
http://www.homeandlearn.org/vba_charts_sheets.html

List of Files:
https://trumpexcel.com/list-of-file-names-from-a-folder-in-excel/



Excel VBA Course Lesson 1: Introduction to VBA and Recording Macros
 Lesson 2: The VB Editor
Lesson 3: Writing VB Code - Introduction to Variables, Decision and Looping Controls Lesson
4: Graceful Error Handling Lesson
5: Excel Functions, User Defined Functions, and Workbook Events Lesson
6: Object Variables, Array Variables, Indefinite Loops Lesson
7: User Forms and Controls Lesson
8: Excel Resources

Vba (Visual Basic) Programming.
Custom Access Database Design And Development.
Spreadsheet Design And Editing.
We Can Build Your Solution In Excel, Access, Mssql, Mysql, Oracle, And More.
Output Reports In Almost Any Format. (Pdf , Excel, Word, Etc)
Automate Time-Consuming Process In Excel Or Access
With Macros And Vba (Visual Basic For Applications)
Routines, Saving You Hours Of Time Doing Labor Intensive
Tasks.


We Assist Small Businesses By Creating Solutions In Microsoft Excel And Access.
• Automate Reporting
• Write Macros To Improve Your Workflow
• Cleanup Outdated Data
• Create Custom Forms Or Surveys (For Internal Or External Use)
• Build Customer Relationship Management (Crm) Systems
• Build Databases

Over Five Years' Experience Creating Solutions For Companies Large And Small.

Successful Projects Include Building A Tracking Database For A Start-Up Drug-Testing Laboratory, Creating A Customer Relationship Management System For An Oil & Gas Services Company, And Developing A Custom Macro To Assist With The Collection Of Data And Automation Of Processes.

Key Words: Excel, Access, Word, Outlook, Vba, Sql, Programming, Programmer, Customized, Ms, Mso, Microsoft, Solutions, Graph, Chart, Module, Report, Designer, Design, Writing, Report Writing, Automate, Workbook, Worksheet, Database, Code, Function, Consultant, Free-Lance, Macro, Analysis, Query, Spreadsheet, Tool, Table, Crm, Customer Relationship Management

Do you need your business to run more efficiently?

I have been developing custom Microsoft Access datatbase and SQL Server database applications in and around the New York area for over 15 years. From small businesses to Not For Profit Organizations to large corporations, my work has saved my client's time and money. I have done work for such companies as ABC, among others. I have experience in the following fields: Accounting, CRM Systems, Hedge Funds, Trading Systems, Budgeting, Inventory, Medical Recordkeeping, and many other diversified experiences.

Many companies have their business spread out in different formats using different programs. I will combine your business into one program, thus making your business run more efficiently. A professionally developed client server Access application can save your company time and money.

For most small and medium projects, Access provides all the tools and facilitates rapid development. Many times companies try to develop these type of applications in-house and run into multiple problems. I can take a project that was started and complete it in a timely fashion. I can develop applications from scratch, or upgrade existing applications, or convert a current program into Access.

My applications are solidly coded using object-oriented VBA techniques, DAO, ADO, ODBC, etc. not a collection of macros. This includes installation of the program and I will provide training and documentation if requested.

My work will save your company time and money and that is the bottom line. Also include a brief description of your project.

EXCEL FOCUSED
*** Automatic emails sent utilizing excel and outlook with the ability to send 100s at a time.
*** Macros to reduce daily processes spent on timely tasks.
*** Customized, automated, & streamlined reporting from small and large data sets

FINANCE FOCUSED
*** Financial modeling and analysis
*** Preparing business analysis and building valuation models to receive capital
*** Quoting and pricing tools that incorporate the use of forms

STUDENT/NEW JOB FOCUSED
*** Projects and assignment
*** Prove-It Tests
*** Tutoring

Tutoring/Learning/Sessions/Class on: Learn how to convert Excel/VBA to Google Sheets GAP (Google App Script)

Tutoring/Learning/Sessions/Class on: Learn how to convert Excel/VBA to Google Sheets GAP (Google App Script)

Seasoned tutor with excellent attitude to help new learners.
I am teaching a course on VBA to GAS conversions. Have experience in training tutoring mentoring 100s of students in analytics. Taken courses and developed courses for various online course providers.

Class 1 Topic of Teaching/tutoring:
Can you run macros on Google Sheets?
You can run macros in Google Sheets, as long as they're written in Google Apps Script, a JavaScript-based language built into Google Apps.
You cannot directly run Excel macros in Google Sheets. Although, You can rewrite the scripts in Google Apps Script.

Class 2: Application of GAS for Cloud Engineering &amp; Changing of Investment Analytics

Class 3:
VBA vs Google Sheet programming and Automation - evolving landscape
Batch file / Command line - simultaneous editing of tens of thousands of files on Google drive
Access the spreadsheet and run macro on any device
Cloud compiling and parallel editing of data - Code to be compiled and parallely on the cloud
Scraping of Data from Internet (Like Factset S&amp;P) and putting it on Cloud or using Google finance or apps
Automation and Volatility trading - changing volatility and portfolio balancing

Class 4: Custom class based on students requirement: Is your company switching from Office to Google Docs and you want to learn it?
Example topics for the tutoring session:
Customer 1: I had this (several) code I want to use in Google Spreadsheets but I have no idea on how to do that.
Customer 2: Had great problems when I wrote about starting my effort to convert a complex VBA project to Google Apps Script. Just wanted to emulate a few VBA functions and do a little tweaking.

Class 5: Summary, revision an samples:
Migrating Excel VBA Macros to Google Sheets/Apps Script: Data reshaping in columns and rows.
One of the things to remember when moving from the Excel to the Google Sheets is that:
Every interaction you make with a spreadsheet comes with a performance hit.
Also Apps Script has a 5-10 minute execution limit and other quotas to consider.

Email me at info@qcfinance.in

office automation excel consultant

http://www.excelconsultant.net/solutions/


http://expertexcelconsultants.com/excel-vba-help/#.WUJoPDgzp1s


Small:

http://1-excel-automation-expert-usa.com/new-york-city-ny-ms-excel-automation.htm

Calling Python from Java Script

Calling Python from Java Script

https://developers.google.com/apps-script/guides/rest/api

https://stackoverflow.com/questions/41048109/launching-python-script-from-google-apps-script?noredirect=1&lq=1


https://stackoverflow.com/questions/22926456/trigger-python-code-from-google-spreadsheets

GAS

Google developer - play with it while you made the changes

https://developers.google.com/analytics/solutions/articles/reporting-apps-script


https://zapier.com/learn/google-sheets/google-apps-script-tutorial/

Create contact with Google Sheets

Project to Make data tables from google sheets

https://ctrlq.org/code/20001-find-rows-in-spreadsheets