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Updated in [March 06th, 2023]
You will gain a comprehensive understanding of the Julia language and its capabilities, enabling you to use it for scientific computing, data analysis, and general-purpose programming. You will also be able to use the Jupyter notebook to create interactive documents and share your work with others. You will be able to use the various Julia packages to create visualizations, manipulate data, and perform statistical analysis. Finally, you will be able to use the Julia language to create your own programs from scratch.
[Applications]
Upon completion of this course, users can apply their knowledge of Julia Scientific Programming to a variety of applications. These applications include data analysis, machine learning, web scraping, and more. Additionally, users can use the Jupyter notebook to create interactive documents that combine code, visualizations, and narrative text. Furthermore, users can use the various Julia packages such as Plots, DataFrames, and Stats to create powerful visualizations and analyze data.
[Career Paths]
1. Data Scientist: Data Scientists use Julia to analyze large datasets and uncover insights. They use Julia to develop predictive models, build machine learning algorithms, and create visualizations. Data Scientists also use Julia to develop applications that can be used to automate processes and make decisions. As data science continues to grow in importance, the demand for Data Scientists with Julia experience is expected to increase.
2. Machine Learning Engineer: Machine Learning Engineers use Julia to develop and deploy machine learning models. They use Julia to create algorithms that can be used to automate processes and make decisions. As machine learning becomes more important in the industry, the demand for Machine Learning Engineers with Julia experience is expected to increase.
3. Research Scientist: Research Scientists use Julia to develop and deploy scientific models. They use Julia to create algorithms that can be used to analyze data and uncover insights. As research continues to grow in importance, the demand for Research Scientists with Julia experience is expected to increase.
4. Software Developer: Software Developers use Julia to develop applications and websites. They use Julia to create algorithms that can be used to automate processes and make decisions. As software development continues to grow in importance, the demand for Software Developers with Julia experience is expected to increase.
[Education Paths]
Recommended Degree Paths:
1. Bachelor of Science in Computer Science: This degree program provides students with a comprehensive understanding of computer science principles and their application to the development of software and hardware systems. Students will learn the fundamentals of programming, data structures, algorithms, operating systems, computer networks, and software engineering. They will also gain experience in developing applications for mobile devices, web development, and artificial intelligence. This degree is ideal for those interested in pursuing a career in software engineering, computer programming, or computer science research.
2. Master of Science in Data Science: This degree program focuses on the application of data science principles to solve real-world problems. Students will learn the fundamentals of data analysis, machine learning, and artificial intelligence. They will also gain experience in developing data-driven applications and using data to inform decision-making. This degree is ideal for those interested in pursuing a career in data science, analytics, or data engineering.
3. Master of Science in Artificial Intelligence: This degree program focuses on the development of intelligent systems and their application to solve real-world problems. Students will learn the fundamentals of artificial intelligence, machine learning, and natural language processing. They will also gain experience in developing intelligent applications and using AI to inform decision-making. This degree is ideal for those interested in pursuing a career in artificial intelligence, machine learning, or robotics.
4. Doctor of Philosophy in Computer Science: This degree program provides students with a comprehensive understanding of computer science principles and their application to the development of software and hardware systems. Students will learn the fundamentals of programming, data structures, algorithms, operating systems, computer networks, and software engineering. They will also gain experience in developing applications for mobile devices, web development, and artificial intelligence. This degree is ideal for those interested in pursuing a career in computer science research or academia.
Developing Trends:
1. Cloud Computing: Cloud computing is becoming increasingly popular as a way to store and access data. This technology allows users to access data from anywhere in the world, and it is becoming increasingly important for businesses to use cloud computing to store and access their data.
2. Machine Learning: Machine learning is a type of artificial intelligence that allows computers to learn from data and make decisions without being explicitly programmed. This technology is becoming increasingly important for businesses to use in order to make decisions quickly and accurately.
3. Natural Language Processing: Natural language processing is a type of artificial intelligence that allows computers to understand and process human language. This technology is becoming increasingly important for businesses to use in order to process customer inquiries and provide accurate responses.
Course Syllabus
Welcome to the course
A warm welcome to Julia Scientific Programming. Over the next four weeks, we will provide you with an introduction to what Julia can offer. This will allow you to learn the basics of the language, and stimulate your imagination about how you can use Julia in your own context. This is all about you exploring Julia - we can only demonstrate some of the capacity and encourage you to take the first steps. For those of you with a programming background, the course is intended to offer a jumpstart into using this language. If you are a novice or beginner programmer, you should follow along the simple coding but recognising that working through the material will not be sufficient to make you a proficient programmer in four weeks. You could see this as the ‘first date’ at the beginning of a long and beautiful new relationship. There is so much you will need to learn and discover. Good luck and we hope you enjoy the course! Best wishes, Henri and JuanA context for exploring Julia: Working with data
In our case study we use Julia to store, plot, select and slice data from the Ebola epidemic. Taking real data, we explain how to work in Julia using arrays, and for loops to work with the structures. By the end of this module, you will be able to: create an array from data; learn to use the logical structures IF and FOR ; conduct basic array slicing, getting the incidence data and generating total number of cases; use Plots to generate graphs and plot data; and combine the Ebola data outputs to show a plot of disease incidence in several countries.Notebooks as Julia Programs
in this week, we demonstrate how it is possible to use Julia in the notebook environment to interpret a model and its fit to the data from the Ebola outbreak. For this, we apply the well-known SIR compartmental model in epidemiology. The SIR model labels three compartments, namely S = number susceptible, I =number infectious, and R =number recovered. By the end of this module, you will be able to: understand the SIR models; describe the basic parameters of an SIR model; plot the model-predicted curve and the data on the same diagram; adjust the parameters of the model so the model-predicted curve is close (or rather as close as you can make it) to the data.Structuring data and functions in Julia
As a scientific computing language, Julia has many applications and is particularly well suited to the task of working with data. In this last module, we will use descriptive statistics as our topic to explore the power of Julia. You should see this week as offering you a chance to further explore concepts introduced in week one and two. You will also be introduced to more efficient ways of managing and visualizing your data. We have also included additional, honors material for those who want to explore further with Julia around functions and collections. By the end of this module, you will be able to: 1. Practice basic functions in Julia 2.Creating random variables from data point values 3. Build your own Dataframes 4. Create a variety of data visualisations 5. Conduct statistical tests 6. Learn how to export your data.
