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Introduction to Data Science with Python

Learn core Python programming, work with libraries such as pandas and Matplotlib, and learn data management, analysis, and visualization through practical projects.

4.6
85 lessons
1 project
4h 10min
Created by Dr. Junaid Qazi
Introduction to Data Science with Python
What's included
  • 85 lessons across 11 modules
  • 7 quizzes with instant feedback
  • 1 project in preconfigured environments
  • AI Tutor on every lesson
Who wrote it
Dr. Junaid Qazi
Dr. Junaid Qazi is a subject matter specialist, data science, machine learning and blockchain consultant. He is a team builder, advisor, professional development coach, mentor, author, technical writer, and invited speaker in his domain of expertise.

Dr. Qazi has a BS with major in Maths, Statistics & Physics. He holds, MS in Computer Science, Professional Master's in Big Data, and a Ph.D. degree. As a mentor and a research scientist, with over 20 years of professional experience, Dr. Qazi has developed a skillset in data cleaning/mining, data analysis & data modelling, machine learning, project management, teaching & training, and career advising while working with academic and industrial giants. Dr. Qazi has also served in academia for several years at the rank of lecturer and assistant professor. During his career, he won several funding awards for his research ideas and published high-quality articles in well-reputed international journals in collaboration with leading scientists from the University of British Columbia, Canada; University of Calgary, Canada; Uppsala University, Sweden; Institut Laue-Langevin (ILL), France; European Synchrotron Radiation Facility (ESRF), France; Diamond Light Source, UK; ISIS Neutron and Muon Source, UK; Unilever, UK; NIST Centre for Neutron Research, USA. He has developed algorithms and written computer codes for his published work. As an invited speaker, Dr. Qazi has delivered several lectures around the globe to the scientific and business community. His diverse academic background along with his educational journey across Asia, Europe, and North America has honed Dr. Qazi with adaptability, determination, and internationalization. As a passionate professional, He has always been ready to learn new techniques to fulfill the needs of his students. He has participated in several professional trainings on teaching and project management. Now, Dr. Qazi believes that he can use his experience to help his students acquire the skills to analyze data, present data stories with beautiful visualizations, and develop machine-learning models to facilitate industry leaders in decision-making. Dr. Qazi looks forward to seeing you in his course on Data Science and Machine Learning. Good Luck! P.S. Dr. Qazi can be reached via LinkedIn for more information on in-person and group training. [https://www.linkedin.com/in/jqazi/]

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What You'll Learn

  • A deep familiarity with various data functions of Python
  • The ability to visualize statistical data using Matplotlib and Plotly libraries
  • A working knowledge of the pandas and NumPy libraries for data cleaning and analysis
  • A strong proficiency in the basics of data science and the Python programming language

Learning Roadmap

85 Lessons7 Quizzes11 Challenges

3.

NumPy: Data Analysis

NumPy: Data Analysis

10 Lessons

10 Lessons

Work your way through NumPy essentials, manipulating arrays, and performing boolean masking and arithmetic operations.

4.

Pandas: Data Analysis

Pandas: Data Analysis

12 Lessons

12 Lessons

Apply your skills to manipulate, clean, merge, and analyze data using pandas efficiently.

5.

Matplotlib: Data Visualization

Matplotlib: Data Visualization

11 Lessons

11 Lessons

Deepen your knowledge of using Matplotlib for creating and customizing data visualizations.

6.

Seaborn: Statistical Data Visualization

Seaborn: Statistical Data Visualization

14 Lessons

14 Lessons

Focus on mastering statistical data visualization using seaborn’s diverse plotting capabilities.

7.

Pandas: Data Visualization

Pandas: Data Visualization

5 Lessons

5 Lessons

Practice using pandas’ robust data visualization tools to create professional, customized plots.

8.

Plotly: Interactive Data Visualization

Plotly: Interactive Data Visualization

3 Lessons

3 Lessons

Try out Plotly for creating interactive visualizations and geographical plotting using maps.

9.

Project 1: Oil vs. Banks During Recession

Project 1: Oil vs. Banks During Recession

7 Lessons

7 Lessons

Get started with analyzing bank and oil stocks using EDA, visualizations, and moving averages.

10.

Project 2: Emergency Calls Dataset

Project 2: Emergency Calls Dataset

7 Lessons

7 Lessons

Work your way through emergency call data analysis with advanced visualization techniques.
Certificate of Completion
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Fahim Ul HaqIntroduction to Data Sciencewith PythonFounder & CEO
About this course
WHY I WROTE THIS COURSE
Python is a widely used programming language for data science and analytics. It is used in industries such as finance, healthcare, and technology. It has a simple syntax, supports multiple programming paradigms, and provides libraries for statistical analysis and data visualization. This course is a comprehensive introduction to statistical analysis using Python. You’ll start with a step-by-step guide to the fundamentals of programming in Python. You’ll learn to apply these functions to numerical data. You’ll first look at strings, lists, dictionaries, loops, functions, and data maps. After mastering these, you’ll take a deep dive into various Python libraries, including pandas, NumPy, Matplotlib, seaborn, and Plotly. You’ll wrap up with guided projects to clean, analyze, and visualize unique datasets using these libraries. By the end of this course, you will be proficient in data science, including data management, analysis, and visualization.
ABOUT THE AUTHOR

Dr. Junaid Qazi

Dr. Junaid Qazi is a subject matter specialist, data science, machine learning and blockchain consultant. He is a team builder, advisor, professional development coach, mentor, author, technical writer, and invited speaker in his domain of expertise.

Learn more about Dr.

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