Learn the best practice for effective data analysis and machine learning with this practical training about data science with Python. Explore how Python can help you take the next step in your Data & AI career, guided by GoDataDriven’s Data Science experts in this 3-days course.

 Video Link: https://www.youtube.com/watch?v=gCH1f0r2iN8

https://godatadriven.com/training/data-science-python-foundation-training/

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Course Description

The training courses in this journey teach you new skills and empower you to stay ahead professionally. We offer solid fundamentals that apply to practical Python courses, whether you are a beginner or an advanced user. We also offer courses on Spark, R, and Deep Learning. Our learning journeys are designed to find the perfect balance between the theory from university with the intensity of a bootcamp. These ingredients are blended into a training format that fits anyone preferred style of learning. You might not start a Ph.D. after one of our courses, but you won’t need to take a three-month sabbatical to become proficient either. We teach you enough theory to know when you’re playing with fire, but we focus on applicability for your job. We’ve experienced first hand what works and what doesn’t through our consulting business, and we pass that knowledge on to you through our education business. You learn all the ins and outs of the data science models most seen in the field, in a fast-paced classroom training that ups your game.

Course Features

What will you learn

» How to set up your Python environment using conda, package managers, and virtual

environments

» The Python ecosystem of different collection types

» How to write Python functions

» About pandas in a global overview, including the index, series, and dataframe types

» How to wrangle and visualize your data with Pandas

 Syllabus

_ Day 1 – Python Foundations

» Hello World in Python

» Interacting with Python through the shell, scripts, and Jupyter Notebooks

» Basic Python elements, such as lists, sets, dictionaries, and tuples

» Usage of variables, functions, and objects

» Introduction to object-oriented programming

 _Day 2 – Pandas

» Basic operations and aggregations

» Building pipelines in pandas

» Data visualization with pandas

 

Pre-requisite

Python for Data Analysts is a foundation training; no previous knowledge of Python is required.

This training requires a laptop. The hands-on labs are run in an online environment, eliminating the

need to install software.

Virtual Classroom

 

  Upcoming Batches

 Why Choose Xebia?

Xebia Academy Global (XAG) is a world-class training & education division of Xebia Group—empowering students & upskilling the workforce. Xebia Academy global has become a leading provider of professional certification & training solutions & maintains global training partner accreditation with over 50 globally recognised bodies such as Microsoft, Cloudera, Hortonworks, Scaled Agile, DASA, UiPath & many others in Digital Technology space worldwide. Technologists from across 100+ countries including aspirants from the world’s leading Fortune 500 companies are using Xebia’ s learning methodology to grow their career.

It’s your business. We accelerate it. As part of Xebia Group, an international boutique network of specialists at the forefront of the digital economy, we combine the best of our company's thinking and experience from the field in our training courses, unlocking tomorrow's skills and capabilities. Our specialist trainers, learning experience and flexible solutions make Xebia Academy a concept to work and live by.

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Meet Our Instructors

 James Hayward

(Data Educator)

 James holds a Master’s degree in Artificial Intelligence from the University of Amsterdam (Cum Laude); a Master’s in Educational Leadership from UCL (Merit); and a Bachelor’s degree in Mathematics from the University of Manchester (First Class Honours). He is fluent in Python and its data science libraries, such as Pandas and Sci-kit Learn, and is proficient with the deep learning frameworks PyTorch and TensorFlow.

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