It is indisputable that skills in Python and data science are in high demand today, and in many ways, these skills are now often a gateway to a fast-track career in both technology and business. While it is a highly flexible and powerful programming language, the beauty of Python lives in the fact it is easy to learn, easily written, and executed much faster than other programming languages. In this course, we take you through the foundations of Python, and then into its application in data science.
It is indisputable that skills in Python and data science are in high demand today, and in many ways, these skills are now often a gateway to a fast-track career in both technology and business. While it is a highly flexible and powerful programming language, the beauty of Python lives in the fact it is easy to learn, easily written, and executed much faster than other programming languages. In this course, we take you through the foundations of Python, and then into its application in data science.
Skills You Will Gain
Big Data
Data Analysis
Pandas
Python
Learning Outcomes (At the end of this program you will be able to)
Understand the object model of Python
Leverage the REPL
Master math with Python
Understand Unicode and string manipulation
Use conditionals and loops
Master the basic data structures like lists and dictionaries
Create functions to enable code reuse
Learn how to slice sequences
Understand how to create and leverage classes
Learn about exceptions and exception handling
Create environments and load libraries
Who Should Attend
Professionals looking to develop a solid understanding of Python and its use in the data science field.
Curriculum
Instructors
Frequently Asked Questions
How much do the courses at Starweaver cost?
We offer flexible payment options to make learning accessible for everyone. With our Pay-As-You-Go plan, you can pay for each course individually. Alternatively, our Subscription-Based plan provides you with unlimited access to all courses for a monthly or yearly fee.
Do you offer any certifications upon completion of a course at Starweaver?
Yes, we do offer a certification upon completion of our course to showcase your newly acquired skills and expertise.
Does Starweaver offer any free courses or trials?
No, we don't offer any free courses, but we do offer 5-day trial only on our subscriptions-based plans.
Are Starweaver's courses designed for beginners or advanced students?
Our course is designed with three levels to cater to your learning needs - Core, Intermediate, and Advanced. You can choose the level that best suits your knowledge and skillset to enhance your learning experience.
What payment options are available for Starweaver courses?
We accept various payment methods such as major credit cards, PayPal, wire transfer, and company purchase orders. For more information related to payments contact customer support.
Do you offer refunds?
Yes, we do offer a 100% refund guarantee for our courses within a specified time frame. If you are not satisfied with the course, contact our customer support team to request a refund with your order details. Some restrictions may apply.
*Where courses have been offered multiple times, the “# Students” includes all students who have enrolled. The “%Recommended” shown is also based on this data.
This Pandas course prepares teaches the fundamentals of data analysis. It shows how to load data, inspect it, deal with missing values, use statistical summaries, plot, pivot and more. This course contains 18 hours of materials, taught by Matt Harris
In the course, we will cover all the foundational concepts needed to begin your journey in data science, and business analytics and learn the concepts and techniques required to use statistics effectively to make better decisions.
In this course, you will be introduced to the DataFrame and the Series, the two primary containers of data within pandas. You will learn the components of these objects and a few basic operations and also know what subset selection methods you should
1Module 0 - Introduction
2Module 1 - Descriptive Statistics
3Module 2 - Cleaning Data
4Module 3 - Visualizing Data
5Module 4 - Sampling
6Module 5 - Probability
Theodore Petrou
Theodore Petrou is the founder of Dunder Data and a leading educator in the fields of data science and machine learning. With a deep passion for teaching and a strong command of Python programming, he has authored several influential books, including Master Data Analysis with Python, Master Machine Learning with Python, Master the Fundamentals of Python, and the popular Pandas Cookbook. Through Dunder Data, Theodore has delivered customized corporate training to renowned organizations such as Microsoft, NASA, and the Federal Reserve, equipping thousands of professionals with practical, hands-on expertise.
With a rich background that bridges both industry and academia, Theodore brings a wealth of experience to his teaching. His career has included roles as a Quantitative Developer, Lead Data Scientist, and Credit Risk Professional, where he solved complex problems in predictive modeling, financial analytics, and data strategy. Alongside developing innovative technical solutions, he has devoted much of his career to mentorship and education, fostering a deep and lasting understanding of data science principles.
Theodore’s teaching extends beyond corporate settings into the broader educational community through live courses and workshops. Known for his clear, engaging style, he breaks down sophisticated concepts in Python and data science to make them accessible and actionable for learners of all levels. His mission is to guide aspiring and experienced professionals alike through the intricacies of data analysis and machine learning with clarity, enthusiasm, and real-world relevance.
With a passion for mathematics and education, Woody Lewenstein has dedicated his career to helping learners of all levels achieve their mathematical goals. He is the founder of Mathematics with Woody, an initiative that offers tailored online mathematics courses designed to support school students preparing for A-levels, as well as adults looking to reskill or enhance their mathematical expertise for industry-specific applications.
Woody’s courses are thoughtfully crafted to make complex mathematical concepts accessible and engaging, ensuring that learners not only understand but also apply their knowledge effectively. In addition to his role as an online educator, he brings extensive experience from a range of educational settings.
For nearly seven years, Woody has taught mathematics at Wren Academy, guiding students through their academic journeys with clarity and enthusiasm. He previously taught both mathematics and economics at King's College London Maths School Trust, enriching his instructional approach with a broad perspective on the practical applications of mathematical principles.
Woody’s academic background includes a Bachelor's degree from the University of Oxford, a Master's degree from King's College London, and a Postgraduate Degree in Education from the University of Roehampton. This strong combination of academic excellence and hands-on teaching experience enables him to deliver comprehensive, effective instruction tailored to the diverse needs of his students.
Segment 41 - Simultaneous Boolean Selection of Rows and Column Labels with loc
Segment 42 - Column to Column Comparison
Segment 43 - Filter for Missing Values
Segment 44 -Exercises - Boolean Selection More
Module 2.8 - Filtering with the Query Method
Segment 45 - Introduction to the Query Method
Segment 46 - Column to Column Comparison with Query
Segment 48 - Arithmetic Operations within Query
Segment 49 - Reference Variable Names
Segment 50 - Selecting Columns with Query
Segment 51 - Summary of the Query Method
Segment 52 -Exercises
Module 2.9 - Miscellaneous Subset Selection
Segment 53 - Selecting a Column with Dot Notation
Segment 54 -Selecting Rows with just the Brackets using Slice Notation
Segment 55 - Selecting a Single Cell with at and iat
Module 2.10 - Taking Certification Exam
Segment 56 - Going to Exam Website
Segment 57 - Completing the Exam
Segment 58 - Submitting the Exam
Matt Harrison
With a rich background in Python and Data Science spanning over a decade, I bring a passion for empowering learners to unravel the complexities of programming and data analysis. My journey began with a deep dive into Computer Science at Stanford University, where I honed foundational skills that underpin my expertise today. From designing predictive models that classify job postings to architecting scalable systems on AWS and Docker, my hands-on experience extends across diverse domains, including machine learning, natural language processing, and web application development.
My commitment to education extends beyond traditional classrooms. As an instructor, I've crafted engaging courses that demystify Python for Finance and Essentials of Stats with Python, ensuring students grasp both theoretical concepts and practical applications. At the heart of my teaching philosophy lies a belief in fostering critical thinking and problem-solving skills essential for today's data-driven world. I thrive on creating environments where learners of all backgrounds can explore, experiment, and ultimately excel in Python programming, data analysis, and beyond.
In addition to my role as an educator, I'm deeply invested in community engagement and knowledge sharing. Whether speaking at renowned conferences like PyCon and SciPy or contributing to esteemed platforms such as O'Reilly Media and Pluralsight, I continuously seek to push the boundaries of what's possible in Python and Data Science education. My dedication to this field is underscored by a commitment to authenticity and a genuine desire to bridge the gap between theoretical learning and practical application.
