Data Science Stack: Introduction to Numpy, Matplotlib and Pandas
WHEN
9 - 10 AUGUST 2021
WHERE
MS TEAMS
TIME
9.00AM - 1.00PM
RM 450 FOR PROFESSIONALS
10% Discount for Early Bird (until 9 July 2021) / Group / Students
CONTENT SUMMARY
INTRODUCTION
Often one gets the question as a Data Scientist what the Python Data Science Stack actually is and where a beginner should start to learn. The Python ecosystem, especially around topics such as data analytics, data mining, data science, and machine learning is so vast and rich that it confuses many. For such an audience a slide deck is created that starts with pointing out the benefits of the Python language for analytics. Even beginners in Python are addressed by some slides that explain the syntax of Python and how to get started. After that, some slides present the most important packages of the data science stack, namely NumPy, Matplotlib, and Pandas. NumPy is one of the most fundamental libraries in Python and perhaps the most useful of them all. NumPy handles large datasets effectively and efficiently. Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Finally, Pandas is a high-level data manipulation tool and is built on the Numpy package. The key data structure of the Pandas package is called the DataFrame. DataFrames allow you to store and manipulate tabular data in rows of observations and columns of variables. At the end of the course, you will have a solid grasp on NumPy, Matplotlib, and Pandas and how it works in Python.
OBJECTIVES
Upon completion of this course, participants will be able to:
WHO SHOULD ATTEND?
1. Associate Professor Dr Mohd Soperi M Zahid
Mohd Soperi is an Associate Professor at Computer and Information Sciences Department, Universiti Teknologi PETRONAS. He obtained his PhD in Computer Science from University of Wisconsin – Milwaukee, USA in 2009, M Sc in Computer Integrated Manufacturing from Rochester Institute of Technology, USA in 1998 and B Sc in Computer Science from New Mexico State University, USA in 1988. His research interests include Internet and Delay Tolerant routing protocols, Software Defined Networks failure recovery, and Cardiovascular diseases detection using Machine Learning. He has published several journals and conference papers in these areas.
2. Dr Khaleel Hussain
Dr Khaleel Hussain completed his PhD from Universiti Teknologi PETRONAS and Master’s degree in Digital Communication and Networking under the Department of Electronics and Networking and Communication Engineering from Visvesvaraya Technological University (VTU), India in 2014. Prior to his Master’s, he has completed his Bachelor’s degree in Electronics and Communication Engineering from VTU in 2012. His research interest lies in the field of Wireless Communications (Routing protocols, receiver-based mechanism, Software Defined Networks and reliable data transmissions), and Machine Learning algorithms.
*fee quoted does not include SST, GST/VAT or withholding tax (if applicable)
*fee quoted does not include SST, GST/VAT or withholding tax (if applicable)
Centre for Advanced & Professional Education (CAPE)
Level 16, Menara 2,
Menara Kembar Bank Rakyat,
50470, Jalan Travers,
Kuala Lumpur.
+605 - 368 7558 /
+605 - 368 8485
cape@utp.edu.my