Data Analytics with Python

A 20-hour remote data analytics with python course. Designed for beginner to intermediate level participants.

Data analysis is key to the success of almost every company and every sector of the economy. With more available every day, the capacity to collect, store, analyze, interpret, and communicate this data effectively is critical to the performance of any organization. Used to inform strategy, improve quality, reach audiences, manage operations, and track finances, data analytics is a core competency in the workforce. In this 20-hour course sequence, you will get the skills you need to succeed in the booming information technology and analytics marketplace. Learn how to gather, prepare, and analyze data with Python – the most important and sought after programming language in the field of information technology and analytics today.

Daily Challenges faced:

• As a data analytics professional, you will face many challenges throughout your working day …
• Data is hard to get – sometimes the databases you use will not make sense, or the data is not available.
• Data is messy – most of the time, data is not in an easily available or useable format.
• Manual tasks – whenever possible, we should try to automate our tasks to reduce redundancy.

Why Use Python:

• Python can work on very large datasets – with ease! It makes analyzing data from a few thousand rows to a few million rows very easy.
• It can perform complex operations – from machine learning, to web development.
• Python’s code can be saved and re-run – making processes automated and a huge time saver.

Course Objectives

• Variable assignments and data types
• Data Structure: Lists, Dictionaries, Sets, Tuple
• Conditional Operations: If Statements, else, elif
• Logical Operations: AND, OR, NOT Functions
• Built-in Functions and Custom Functions
• NumPy
• Pandas
• Matplotlib, Seaborn
• Data wrangling
• Regression

Project Information

• Analyze Covid-19 dataset and gain insights from underlying data
• Perform stock data analysis using various data analysis libraries
• Perform analysis on CDC data to answer questions such as: does the data show significant evidence that certain demographic groups are more prone to diabetes? How and does diabetes impact the length of stay in a hospital?
• Perform analysis on various tasks and activities performed by a data analyst professional and summarize the analysis

Included in the Course:

• Certificate/ badge of completion
• Data analytics E-Book
• GitHub Profile
• 2 personal Data Analytics projects published onto GitHub
• Mentorship and career advice

Course Details:

The data analytics course will meet Monday – Thursday (4 days a week) beginning on Monday, March 22, 2021 until Thursday, April 1, 2021.

About the Trainer:

Imran Khan is trained in business administration, applied urban science and informatics, public policy, education, and biochemistry. He has served as a policymaker and in project management roles in federal, state, and local government. From 2013 to 2015, he served as an Empire State Fellow in New York State government. In 2011, he worked as an Education Pioneers fellow in Houston, his hometown. Imran’s professional interests and areas of expertise include data science, human-centered design and user experience, materials science and engineering, operations research, and statistics. Currently, he works as an engineer at Build Well Labs.