Python Data Science Fundamentals: Getting Started

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Academy of Computing & Artificial Intelligence

1:59:26

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1 - Introduction

1 - Introduction to Course Python Data Science Fundamentals Getting Started.mp4

05:34

2 - Welcome Note by the Author.html

3 - Prerequisite for This Course Embark on Your Data Science Journey.mp4

00:59

2 - Setting up the Environment

4 - Download and Install Anaconda Environment.mp4

08:06

3 - Introduction to NumPy Foundations of Numerical Computing

5 - Introduction to NumPy.mp4

02:08

6 - Create a NumPy ndarray Object.mp4

10:02

7 - NumPy Array Indexing.mp4

09:02

8 - NumPy Array Slicing Numerical Python.mp4

04:48

9 - NumPy Array Copy vs View Numerical Python.mp4

06:09

10 - NumPy Array Reshaping Numerical Python.mp4

06:29

11 - NumPy Array Iterating Numerical Python.mp4

03:31

4 - Introduction to Pandas A Powerful Data Analysis Library

12 - Pandas Introduction.mp4

00:49

13 - Pandas DataFrames.mp4

03:22

14 - Pandas Read CSV & Analyzing DataFrames.mp4

06:18

15 - Pandas Cleaning Empty Cells.mp4

03:49

16 - Pandas Removing Duplicates.mp4

03:10

17 - Pandas Data Correlations.mp4

05:24

5 - Matplotlib Tutorial

18 - Matplotlib Tutorial Part 1.mp4

11:30

6 - Scikitlearn Essentials Pythons ML Powerhouse Getting started

19 - Python Machine Learning ScikitLearn Getting started.mp4

12:30

20 - Python Machine Learning ScikitLearn Data Preprocessing.mp4

08:38

21 - Python Machine Learning ScikitLearn Model Training.mp4

07:08

22 - Python Machine Learning ScikitLearn Model Building & Evaluation.html

Description

Python Data Science Fundamentals: Dive into NumPy, Pandas, Matplotlib, and Scikit-learn for Powerful Data Insights

What You'll Learn?

Master data analysis using NumPy & Pandas for efficient manipulation
Create impactful data visualizations with Matplotlib, conveying insights effectively
Gain an introduction to Scikit-learn, building and evaluating predictive models
Enhancing practical skills in data analysis, visualization, & basic machine learning techniques

Who is this for?

Beginners with basic programming experience looking to enter the field of data science.

Aspiring data analysts or data scientists seeking to build a strong foundation in Python for data manipulation and analysis

Professionals from diverse backgrounds aiming to enhance their data analysis and visualization skills

Individuals interested in understanding the basics of machine learning and its applications in real-world scenarios

What You Need to Know?

Computer/ Mobile

Basic Python Knowledge

More details

Description
Course Description: Python for Machine Learning: A Beginner's Kickstart
Welcome to the Python for Machine Learning: A Beginner's Kickstart course! This introductory course is designed to provide you with the fundamental skills and knowledge needed to dive into the exciting world of machine learning using Python.
Course Overview: In this course, you'll gain hands-on experience with essential Python libraries for data manipulation, analysis, visualization, and machine learning. The course focuses on three core libraries: NumPy, Pandas, Matplotlib, and Scikit-learn. These libraries are the backbone of data science and machine learning in Python, and mastering them will give you a solid foundation to explore more advanced machine learning topics.
What You'll Learn:
NumPy: Learn how to efficiently work with arrays and matrices, perform mathematical operations, and manipulate data in Python using NumPy.
Pandas: Discover the power of Pandas for data wrangling and manipulation, from handling data frames to performing data analysis and cleaning.
Matplotlib: Explore data visualization techniques using Matplotlib to create meaningful plots and charts.
Scikit-learn: Dive into the world of machine learning with Scikit-learn. Understand the basics of data preprocessing, model building, training, evaluation, and prediction.
Launch Your Data Science Journey: Embark on a transformative learning journey that will equip you with the fundamental skills and knowledge needed to excel in the field of data science. With Python at the heart of this course, you'll harness the power of NumPy, Pandas, Matplotlib, and Scikit-learn to become a proficient data scientist.

Why Start Here: This course is designed to be your first step into the thrilling world of data science and machine learning. We'll take you on a beginner-friendly adventure, focusing on essential Python libraries: NumPy for numerical computing, Pandas for data manipulation, Matplotlib for data visualization, and Scikit-learn for introductory machine learning.
Build Essential Skills: Discover the power of Python in data science as we guide you through the fundamental concepts of each library. By the end of the course, you'll have a solid understanding of how to perform basic data analysis, visualization, and even create simple machine learning models.
Who this course is for:
Beginners with basic programming experience looking to enter the field of data science.
Aspiring data analysts or data scientists seeking to build a strong foundation in Python for data manipulation and analysis
Professionals from diverse backgrounds aiming to enhance their data analysis and visualization skills
Individuals interested in understanding the basics of machine learning and its applications in real-world scenarios

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Academy of Computing & Artificial Intelligence -UK proudly presents you these valuable courses. [ACAI]It all started when the expert team of The Academy of Computing & Artificial Intelligence [ACAI] (PhD, PhD Candidates, Senior Lecturers , Consultants , Researchers) and Industry Experts . hiring managers were having a discussion on the most highly paid jobs & skills in the IT/Computer Science / Engineering / Data Science sector in 2022. To make the course more interactive, we have also provided a live code demonstration where we explain to you how we could apply each concept/principle [Step by step guidance]. Each & every step is clearly explained. [Guided Tutorials]"While artificial intelligence (AI) is the broad science of mimicking human abilities, machine learning is a specific subset of AI that trains a machine how to learn. The Founder has over 12 years of work experience as a Researcher, Senior Lecturer, Project Supervisor & Engineer. PhD Candidate in Australia,MSc Artificial Intelligence (University of Moratuwa), BSc Software Engineering - First Class Honours (University of Westminster),SCJP, SCWCHe has completed a MSc in Artificial Intelligence. Completed BSc Software Engineering - First Class Honors from University of Westminster (UK). Sun Certified Java Programmer (SCJP). – 93% and a Sun Certified Web Component Developer 97%. Research experience in Data mining, Machine Learning , Cloud computing, Business Intelligence & Software Engineering.Course Team includes : PhD Holders , PhD Candidates, Senior Lecturers , Consultants , Researchers, Industry Experts & hiring managers

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