

Our Courses
Python Data Visualization
This if the final course in the specialization which builds upon the knowledge learned in Python Programming Essentials, Python Data Representations, and Python Data Analysis. We will learn how to install external packages for use within Python, acquire data from sources on the Web, and then we will clean, process, analyze, and visualize that data.
-
Course by
-
Self Paced
-
9 hours
-
English
Introduction to Python Programming
This course provides an introduction to programming and the Python language. Students are introduced to core programming concepts like data structures, conditionals, loops, variables, and functions. This course includes an overview of the various tools available for writing and running Python, and gets students coding quickly. It also provides hands-on coding exercises using commonly used data structures, writing custom functions, and reading and writing to files.
-
Course by
-
Self Paced
-
28 hours
-
English
Introduction to Data Science in Python
This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library. The course will introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Series and DataFrame as the central data structures for data analysis, along with tutorials on how to use functions such as groupby, merge, and pivot tables effectively.
-
Course by
-
Self Paced
-
35 hours
-
English
The Raspberry Pi Platform and Python Programming for the Raspberry Pi
The Raspberry Pi is a small, affordable single-board computer that you will use to design and develop fun and practical IoT devices while learning programming and computer hardware. In addition, you will learn how to set up up the Raspberry Pi environment, get a Linux operating system running, and write and execute some basic Python code on the Raspberry Pi. You will also learn how to use Python-based IDE (integrated development environments) for the Raspberry Pi and how to trace and debug Python code on the device. Please note that this course does not include discussion forums.
-
Course by
-
Self Paced
-
11 hours
-
English
Getting started with TensorFlow 2
Welcome to this course on Getting started with TensorFlow 2! In this course you will learn a complete end-to-end workflow for developing deep learning models with Tensorflow, from building, training, evaluating and predicting with models using the Sequential API, validating your models and including regularisation, implementing callbacks, and saving and loading models. You will put concepts that you learn about into practice straight away in practical, hands-on coding tutorials, which you will be guided through by a graduate teaching assistant.
-
Course by
-
Self Paced
-
26 hours
-
English
AI for Medical Diagnosis
AI is transforming the practice of medicine. It’s helping doctors diagnose patients more accurately, make predictions about patients’ future health, and recommend better treatments. As an AI practitioner, you have the opportunity to join in this transformation of modern medicine. If you're already familiar with some of the math and coding behind AI algorithms, and are eager to develop your skills further to tackle challenges in the healthcare industry, then this specialization is for you. No prior medical expertise is required!
-
Course by
-
Self Paced
-
20 hours
-
English
Python Functions, Files, and Dictionaries
This course introduces the dictionary data structure and user-defined functions. You’ll learn about local and global variables, optional and keyword parameter-passing, named functions and lambda expressions. You’ll also learn about Python’s sorted function and how to control the order in which it sorts by passing in another function as an input. For your final project, you’ll read in simulated social media data from a file, compute sentiment scores, and write out .csv files.
-
Course by
-
Self Paced
-
31 hours
-
English
Introduction to Computer Vision and Image Processing
Computer Vision is one of the most exciting fields in Machine Learning and AI. It has applications in many industries, such as self-driving cars, robotics, augmented reality, and much more. In this beginner-friendly course, you will understand computer vision and learn about its various applications across many industries. As part of this course, you will utilize Python, Pillow, and OpenCV for basic image processing and perform image classification and object detection. This is a hands-on course and involves several labs and exercises.
-
Course by
-
Self Paced
-
22 hours
-
English
Python Data Analysis
This course will continue the introduction to Python programming that started with Python Programming Essentials and Python Data Representations. We'll learn about reading, storing, and processing tabular data, which are common tasks. We will also teach you about CSV files and Python's support for reading and writing them. CSV files are a generic, plain text file format that allows you to exchange tabular data between different programs.
-
Course by
-
Self Paced
-
9 hours
-
English
Python Data Representations
This course will continue the introduction to Python programming that started with Python Programming Essentials. We'll learn about different data representations, including strings, lists, and tuples, that form the core of all Python programs. We will also teach you how to access files, which will allow you to store and retrieve data within your programs. These concepts and skills will help you to manipulate data and write more complex Python programs. By the end of the course, you will be able to write Python programs that can manipulate data stored in files.
-
Course by
-
Self Paced
-
9 hours
-
English
Programming in Python
In this course, you will be introduced to foundational programming skills with basic Python Syntax. You’ll learn how to use code to solve problems. You’ll dive deep into the Python ecosystem and learn popular modules, libraries and tools for Python. You’ll also get hands-on with objects, classes and methods in Python, and utilize variables, data types, control flow and loops, functions and data structures.
-
Course by
-
Self Paced
-
45 hours
-
English
Computational Thinking for Problem Solving
Computational thinking is the process of approaching a problem in a systematic manner and creating and expressing a solution such that it can be carried out by a computer. But you don't need to be a computer scientist to think like a computer scientist! In fact, we encourage students from any field of study to take this course. Many quantitative and data-centric problems can be solved using computational thinking and an understanding of computational thinking will give you a foundation for solving problems that have real-world, social impact.
-
Course by
-
Self Paced
-
18 hours
-
English
Customising your models with TensorFlow 2
Welcome to this course on Customising your models with TensorFlow 2! In this course you will deepen your knowledge and skills with TensorFlow, in order to develop fully customised deep learning models and workflows for any application. You will use lower level APIs in TensorFlow to develop complex model architectures, fully customised layers, and a flexible data workflow.
-
Course by
-
27 hours
-
English
Python Programming Essentials
This course will introduce you to the wonderful world of Python programming! We'll learn about the essential elements of programming and how to construct basic Python programs. We will cover expressions, variables, functions, logic, and conditionals, which are foundational concepts in computer programming. We will also teach you how to use Python modules, which enable you to benefit from the vast array of functionality that is already a part of the Python language.
-
Course by
-
Self Paced
-
10 hours
-
English
Python Basics
This course introduces the basics of Python 3, including conditional execution and iteration as control structures, and strings and lists as data structures. You'll program an on-screen Turtle to draw pretty pictures. You'll also learn to draw reference diagrams as a way to reason about program executions, which will help to build up your debugging skills. The course has no prerequisites.
-
Course by
-
Self Paced
-
34 hours
-
English
Python for Genomic Data Science
This class provides an introduction to the Python programming language and the iPython notebook. This is the third course in the Genomic Big Data Science Specialization from Johns Hopkins University.
-
Course by
-
Self Paced
-
9 hours
-
English
Introduction to Portfolio Construction and Analysis with Python
The practice of investment management has been transformed in recent years by computational methods. This course provides an introduction to the underlying science, with the aim of giving you a thorough understanding of that scientific basis. However, instead of merely explaining the science, we help you build on that foundation in a practical manner, with an emphasis on the hands-on implementation of those ideas in the Python programming language.
-
Course by
-
Self Paced
-
25 hours
-
English
Python Data Structures
This course will introduce the core data structures of the Python programming language. We will move past the basics of procedural programming and explore how we can use the Python built-in data structures such as lists, dictionaries, and tuples to perform increasingly complex data analysis. This course will cover Chapters 6-10 of the textbook “Python for Everybody”. This course covers Python 3.
-
Course by
-
Self Paced
-
3 hours
-
English
Python 101: Develop Your First Python Program
In this hands-on guided project, we will learn Python programming fundamentals and build our first program in Python. We will learn understand variables assignment, differentiate between various data types in python such as strings, lists, integer and float, learn the difference between for and while loops, develop functions in python, perform math operations, get information from User and Print data on the screen, and develop a simple game in Python. Note: This course works best for learners who are based in the North America region.
-
Course by
-
Self Paced
-
3 hours
-
English
Prompt Engineering with GPT: Programming for Custom Content
Ever wondered how we can use AI in programing to make our workloads easier? In this 2-hour long project-based course, you will master the art of prompt engineering to design an educational tool using the capabilities of OpenAI's GPT-3 language model. You will be creating a multiple-choice quiz generator using Python and GPT-3. You will write a Python script from scratch that is able to generate a custom multiple-choice exam, capable of dynamically adjusting the topic, number of questions, and number of potential answers.
-
Course by
-
Self Paced
-
2 hours
-
English
Mathematics for Machine Learning and Data Science
Newly updated for 2024! Mathematics for Machine Learning and Data Science is a foundational online program created by DeepLearning.AI and taught by Luis Serrano. In machine learning, you apply math concepts through programming. And so, in this specialization, you’ll apply the math concepts you learn using Python programming in hands-on lab exercises.
-
Course by
-
Self Paced
-
English
Using Python for Research
Take your introductory knowledge of Python programming to the next level and learn how to use Python 3 for your research.
-
Course by
-
Self Paced
-
30
-
English
Statistics for Data Science with Python
This Statistics for Data Science course is designed to introduce you to the basic principles of statistical methods and procedures used for data analysis. After completing this course you will have practical knowledge of crucial topics in statistics including - data gathering, summarizing data using descriptive statistics, displaying and visualizing data, examining relationships between variables, probability distributions, expected values, hypothesis testing, introduction to ANOVA (analysis of variance), regression and correlation analysis.
-
Course by
-
Self Paced
-
14 hours
-
English
Exception Handling in Python
In this 1-hour long project-based course, you will learn the differences between an exception and syntax errors, how to raise an exception, what an AssertionError exception is within Python, how to use the try, except and else clause and how to use the finally clause and any clean-up actions. By the end of this project, you will have an understanding of error and exception handling in python. Once you have a beginner's knowledge of python programming and start coding you may find that something disrupts the normal flow of the program you have built.
-
Course by
-
Self Paced
-
3 hours
-
English
Data Science for Construction, Architecture and Engineering
This course introduces data science skills targeting applications in the design, construction, and operations of buildings. You will learn practical coding within this context with an emphasis on basic Python programming and the Pandas library.
-
Course by
-
5
-
English