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Python Data Analyst   

How would you like to have a high paying career in one of the fastest growing job markets in the United States? This program teaches the skills that are in high demand and can help you advance in a variety of careers. Data Analytics, Data Science, Big Data, Artificial Intelligence, Machine Learning, and Python programming skills are becoming vital for most businesses including Health Care, Insurance, Medicine, Finance, Social Science, Manufacturing, Government and many more. Each year of experience will boost your earnings dramatically year after year.

In 2020, job openings for data scientists and similar advanced analytical roles will reach 61,799. This is a significant number, but it represents just 2% of the projected demand across all job roles requiring data and analytics skills.

The student will earn several recognized certificates including the IBM Data Science Professional Certificate. They will have access to PyCharm, Anaconda, Tableau, Jupyter, R, Pandas and other specialized programs and learning tools. The course will use books, videos, online curriculum, and resources from several vendors, online learning platforms, courses, Programs and Certificate of completion from curated sources will be included in your Tuition.

Online Instructor led classes, assigned reading, videos, and exercises. One-on one mentoring will be available to answer any questions and provide individual technical training when needed. Online live Instructor led hands on instructions with lectures and in-class projects. Upon successful completion of this program, you will earn a Certificate of Completion in the MCC Python Data Analyst Program.

Before you can begin, you must complete 20 hours of pre-program training material. Students will also be required to start an online Python programming training, and a math refresher.

Topics to be covered will include:

Data Analytics with Excel

Student will learn the basics of a database including Pivot Tables, VBA Scripting, VSLookup, Data visualization (Charts, Graphs, and Histograms), data wrangling. Calculations and Analysis.

Python Programming Intro

An introduction to Python. No experience is required. Student will learn data types operators, control flow, functions, scripting. We will learn how to run code and practice our programming skills in the Jupyter and PyCharm programming environments.

Intro to SQL

An introductory course to MySQL. This class introduces SQL Basics (SELECT, JOIN, WHERE), SQL Joins, SQL Aggregations (SUM, MIN, MAX, COUNT, DASE DATE).

Math Refresher

A refresher course in statistics, a review of specific Algebra related to Data Analytics (Venn diagram is related to SQL commands, and Matrices, Linear Regression.

Learning Data Analysis with Python

Learn how to use Python IDE, VSCode, Anaconda, Jupyter, PyCharm, the command line (Terminal, Bash). You will learn how to access many of the popular Data Science libraries available in Python. The Integrated Developer Environments (IDE) will allow one to learn and debug Python efficiently and how to tell a story by visualizing data.

Data Wrangling

We will teach you to Do Data Wrangling using Python and demonstrate data wrangling in R. 80% of a typical data science project is sourcing cleaning and preparing the data, while the remaining 20% is actual data analysis. A data scientist's job is to collect and clean data collect data from a variety of sources including, Social Media sites (Twitter), Excel files (CVS), MySQL, JSON, XML, csv, txt).

Mini Project

We will access an external public database, and create a small project using Excel. This project will introduce the student to fundamental data visualization (Charts, Graphs, Histograms), and consistent data analysis techniques used to produce compelling business solutions.

Git & GitHub

Create a GitHub account. Install Git. Review the concept of version control and give user cases for team collaboration. Review add, commit, clone, push, pull, branch and merge. GitHub comments and GitHub workflows.

Introduction to R and RStudio

R is not only entrusted by academic, but many large companies also use R programming language, including Uber, Google, Airbnb, and Facebook. RStudio is an awesome tool that can help you do your work better and faster. In technical terms, RStudio is a cross-platform integrated development environment (IDE) for the R statistical language.

NumPy, Pandas, Matplotlib

Pandas and NumPy are two Python libraries that are core the field of data analysis. Learn to use Pandas Data Frames, NumPy multi-dimensional arrays. We will use pandas to load, manipulate, analyze, and visualize contemporary datasets.

Business Intelligence Software

You will be introduced to a Python Machine Learning Library called Scikit-Learn: You will also be introduced to Tableau. You will have online resources to continue your learning, participate in open Data Science Projects, and update your professional portfolio. You will have a strong grasp of Data Analytic, and will be ready to work in a professional Data Analytics related job.

Final Project

Your final project will be completed individually. You will use the techniques you learned to create a solution to a real world project using real data. Get creative and come up with something exciting to show off to the whole world.

Courses : Hours:

Data Analytics with Excel 9 Python Programming Intro 12 Intro to MySQL 15 Statistics Math Refresher 15 Learning Statistics with Python 18 Data Wrangling 21 Mini Project 9 Git & GitHub 6 Introduction to R, R studio 9 NumPy, Pandas, Matplotlib, 21 Business Intelligence Software 6 Final Project 6 Program Total 144 Hours

Prerequisites: You will need to be interviewed by one of our program manager to help you decide what program best suits your needs, and objectives. Before you can be admitted into this program, you will need to be enrolled in our free online pre-course work. Please call Gerald Ringer at 1-585-484-7095 for assistance to get started on your pre-program training.


There are no classes currently available.

For inquiries, please call 585.685.6004 to get information regarding future classes.

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