- we will teach you from basics, No Programming background is required.
Training Program Description:
- This 3 -days introduction to Python will kickstart your learning of Python for data science, as well as programming in general. This beginner-friendly Python course will take you from zero to programming in Python in a matter of hours
- In the information age, data is all around us. Within this data are answers to compelling questions across many societal domains (politics, business, science, etc.). But if you had access to a large dataset, would you be able to find the answers you seek?
- Learn to use powerful, open-source, Python tools, including Pandas, Git and Matplotlib, to manipulate, analyze, and visualize complex datasets.
- jupyter notebooks
- This course will introduce you to a collection of powerful, open-source, tools needed to analyze data and to conduct data science. Specifically, you’ll learn how to use:
- and many other tools. You will learn these tools all within the context of solving compelling data science problems.
Audience and Requirements
- The course is suitable for a range of positions including:
- Data analysts
- Software engineers
- A programmer interested in building data science products
- Anyone (researcher, student, professional) learning Data science
- Corporates and start-ups looking to add DS to their product or service offerings
- Hardware: Bring Your Own Laptop and charger, leave with the knowledge
- Important note: Each Bootcamp participant is required to bring their own laptop running Windows 10. Although this workshop requires Windows 10, the skills learned, and code used will be transferrable to Mac OS and other platforms because all software used will be open source.
- Assistants will also be on hand to help attendees with hardware/software issues.
- Attendees receive an electronic copy of the course materials and related code at the conclusion of the Bootcamp.
- This program is comprised of many career-oriented projects. Each project you build will be an opportunity to demonstrate what you've learned in the lessons. Your completed projects will become part of a career portfolio that will demonstrate to potential employers that you have skills in data analysis and feature engineering, machine learning algorithms, and training and evaluating models.
- One of our main goals at EAII is to help you create a job-ready portfolio of completed projects. Building a project is one of the best ways to test the skills you've acquired and to demonstrate your newfound abilities to future employers or colleagues. Throughout this program, you'll have the opportunity to prove your skills by building the following projects
- Building a project is one of the best ways both to test the skills you’ve acquired and to demonstrate your newfound abilities to future employers. Throughout this program, you’ll have the opportunity to prove your skills by building projects during the program
- introduce you to a collection of powerful, open-source, tools needed to analyze data and to conduct data science
- Solving compelling data science problems.
- using python tools to import data, explore it, analyze it, learn from it, visualize it, and ultimately generate easily sharable reports.
- become a member of a world-wide community which seeks to build data science tools, explore public datasets, and discuss evidence-based findings
- Learn How to effectively visualize results
- Receive a Certificate of Completion from Epsilon AI Institute, Delaware, USA
10% Theory, 90% Practice
Program Duration: 3 Days
Program Language: English / Arabic
Location: Online Virtual classroom Live ( Zoom Platform) / Offline (EPSILON AI INSTITUTE | Nasr City)
Participants will be granted a completion certificate from Epsilon AI Institute, USA if they attend a minimum of 80 percent of the direct contact hours of the Program and after fulfilling program requirements (passing both Final Exam and Project to obtain the Certificate)
- Introduction to Computer Science
- Anaconda Environment Setup
- Intro to interpreted languages
- Hello world in python
- Output & Input
- Variables / Data types / Math & Logic
- If Else Statements
- For & While Statements
- Built-in functions and operators
- List Comprehensions
- Map, Filter
- Lambda expressions
- Math & OS module
- OOP Classes
- Errors and Exceptions Handling
- Project – Problem Solving Expo
- Numpy and ND arrays
- Exploratory data analysis
- Machine learning with Scikit-learn
- Project 3 – Forest Fires in Brazil
Download Python 3 for Data Science BOOTCAMP Brochure PDF