Data Analytics

Data analysis is key to the success of almost every company and every sector of the economy. With more and more data available every day, the capacity to collect, store, analyze, interpret and communicate this data effectively to inform strategy, improve quality, reach audiences, manage operations and track finances is critical to the performance of any organization.

Learn how to gather, prepare and analyze data, and study SQL and Python – the most important and sought after skills in the field of information technology and analytics.

SKILLS
At the end of Track 1, you will be able to:		At the end of Track 2, you will be able to:
Create databases, tables, and query data using SQL. Retrieve data from external sources and organize data using Python, including CSV, Excel, and relational databases. Perform data cleaning and transformations in Python using various libraries, including: numpy and pandas Use Python to learn key statistical methods for analyzing data - including: Exploratory data analysis and regression analysis. Visualization and presentation techniques to share conclusions with classmates.		Retrieve data from external sources and organize data using Python, including CSV, Excel, and relational databases. Perform data cleaning and transformations in Python using libraries including: numpy, pandas. Use Python to learn key statistical methods for analyzing data - including: statistical distributions, sampling, and regression. Use Machine Learning to train various type of models to make predictions on large datasets, using scikit-learn. Evaluate their predictions that result from ML techniques, how to access model quality, and improve models over time. Visualization and presentation techniques to share conclusions with classmates.
Track 1: Non-Analyst to Entry-Level Analyst		Track 2: Data Analyst to Senior Analyst
Unit 1: Relational Databases and Data Extraction	40 hours	Unit 1: Relational Databases and Data Extraction	15 hours
Unit 2: Python for Data Analytics	30 hours	Unit 2: Python for Data Analytics	10 hours
Unit 3: Data Analytics & Descriptive Statistics in Python	50 hours	Unit 3: Data Analytics & Descriptive Statistics in Python	50 hours
Unit 4: Data Visualization & Presentations	50 hours	Unit 4: Machine Learning and Modeling Techniques	60 hours
Capstone Project & Presentations	20 hours	Unit 5: Data Visualization & Presentations	50 hours
		Capstone Project & Presentations	20 hours
Total:	190 hours	Total:	205 hours

COURSES
Data Analytics 1: SQL, Python and Tableau (Online)
The ability to gather, prepare, analyze and display data from structured and unstructured sources is one of the most sought after skills in the information technology marketplace, with demand spanning across sectors that include healthcare, finance, retail, real estate and even gaming. Learn to query data using SQL; perform data cleaning and transformations in Python; use key statistical methods to analyze data in Python; and visualize and present data with Tableau. You will complete multiple applied projects throughout the course, including a capstone project in your area of interest. Prerequisite: Basic Excel proficiency.
Mon, Tues, Wed & Thurs 10/18/2020 2/24/2021 6:00-9:00 $2495 A23ANA001A
Data Analytics 2: Machine Learning and Modeling (Online)
Take your data analysis skills to the next level. This course is designed for professionals in the data analytics and data science fields who would like to brush up on their use of SQL, Python and Tableau, and take a deeper dive into machine learning and modeling. Explore using machine learning to train various types of models to make predictions on large datasets. You will complete multiple applied projects throughout the course, including a capstone project in your area of interest. Prerequisite: Data Analytics 1 or passing of an entrance exam that requires some knowledge of R and Python.
Mon, Tues, Wed & Thurs 10/18/2020 3/3/2021 6:00-9:00 $2495 A23ANA001B
REQUIREMENTS

Prerequisites

Prerequisite for Data Analytics 1: SQL, Python and Tableau (Online): Basic Excel proficiency

Prerequisite for Data Analytics 2: Machine Learning and Modeling (Online): Data Analytics 1 or passing of an entrance exam that requires some knowledge of R and Python
CAREER PROFILE

Potential Jobs

LaGuardia’s Data Analytics courses provide a broad foundation of skills that can be applied to a variety of sectors and titles, including management analyst, market research analysts and financial analyst.

Salary

These three occupations have potential wages in the six figures, median wages over $80,000, and entry-level wages over $48,000.

Job Trends

These three occupations encompass almost 100,000 jobs in New York City and an average of over 3,500 annual openings. Over the next decade management analyst jobs are expected to grow by 24% and market research analysts by 28%.

(New York State Department of Labor Occupational Employment Statistics Long-Term Occupational Projections)
PARTNERS
RELATED PROGRAMS

LaGuardia TechHire Open Code

Contact Us

Phone

(718) 482-5300

E-mail

Yaazieli Ortiz Felicie at yortizfelicie@lagcc.cuny.edu

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Ways to Register

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(718) 482-7244
with payment by MasterCard/Visa/Discover/American Express.

Discounts and waivers apply to all courses except those designated ND.

Data Analytics

COURSES

Data Analytics 1: SQL, Python and Tableau (Online)

Data Analytics 2: Machine Learning and Modeling (Online)

REQUIREMENTS

Prerequisites

CAREER PROFILE

Potential Jobs

Salary

Job Trends

PARTNERS

RELATED PROGRAMS

LaGuardia TechHire Open Code

Contact Us

Register

Ways to Register