FINM1001 - Foundations of Finance

This course is designed to familiarise students with the components of the financial system as well as to introduce them to the three basic ideas underpinning finance, namely the time value of money, diversification and arbitrage. Overall, as an introductory course to the finance world, it is quite good and relatively straightforward. Basic concepts are covered, and with some extra practice, it is possible to adequately prepare for exams without investing too much time.

Difficulty level: 1

Worth study: 4

FINM2001 - Corporate Finance

This course focuses on tools and techniques used in modern financial management. Material in the course has an applied focus and is designed to provide students with the knowledge and skills required for understanding, exploring and analysing financial management issues. This course is a step up from FINM1001, but it's still very manageable. It covers basic Excel skills, regression/evaluation models, and statistical analysis. Although it's more challenging, it's definitely doable with consistent effort and practice. I personally don't remember much about this course, which suggests that it's not overly difficult. If you stay on top of the material and put in the work, you should be able to earn a high grade.

Difficulty level: 2

Worth study: 4

FINM2002 - Derivatives

This unit is designed to further understanding of futures and options contracts and their use in managing risk. It builds upon material covered in FINM1001. FINM2002 provides an overview of options, futures, forwards and swaps on a range of underlying assets/commodities including stocks, interest rates, foreign exchange as well as more exotic instruments such as weather and electricity derivatives. This course can be challenging, particularly when it comes to calculations and understanding models. The difficulty level may vary depending on the lecturer. For example, in the semester I took this course in 2020, the exam was extremely difficult. To prepare for the exam, I recommend creating an Excel sheet with all the necessary formulas already filled in. This will save you time during the exam and allow you to focus on the more complex conceptual questions. Overall, while the course may be challenging, with sufficient preparation and hard work, it is definitely manageable.

However, I have heard that the course has become easier in recent years. Nonetheless, I know of a friend who failed the final exam, so it is still important to study and prepare diligently.

Difficulty level: 3.5-4.5

Worth study: 5

FINM2003 - Investments

This course is designed to prepare students for designing investment portfolios. It covers duties to clients, types of investment products, explores links between investment risk and return, introduces tools for use in portfolio construction, brings in analysis of fixed income products and introduces techniques to evaluate past investment performance.

This course is slightly more challenging than FINM1001, but it is still manageable. The course content includes more advanced Excel skills, basic regression models, and statistical analysis. The assessment includes a group report, which requires some effort, but it is not overly difficult. If you are willing to put in the work, you should have some fun.

Difficulty level: 2

Worth study: 3

FINM3005 - Corporate Finance

This course covers advanced topics in corporate finance, including capital structure, capital budgeting, dividend policy, mergers and acquisitions, and corporate governance. Students will also learn to apply the Discounted Cash Flow (DCF) model on a company's annual report for 10 years. The course is relatively challenging as it requires extensive work in Excel and report reading, data entry, Excel calculations, and formatting can be very intensive if group members do not manage their time well. In addition, the group assignment is separated into two parts, so students need to apply themselves to both parts to achieve success.

Difficulty level: 4.5

Worth study: 3

FINM3006 - Financial Intermediation and Debt Markets

This course covers the theory and practice of financial intermediation, broadly construed to include banks, savings institutions and investment/merchant banks. Topics will include the role of banking firms in a developed capital market, their impact on corporate financial decisions for non-banking firms, and the regulation of banks. The course includes a comprehensive analysis of the role of financial intermediaries in the development of fixed-income markets and provides an analysis of fixed income securities. Additional topics include models and techniques used for managing credit risk, interest rate risk and liquidity risk. These are applied to maturity matching, duration and immunization, loan sales, securitization, collateralized debt obligations (CDOs), and collateralized mortgage obligations (CMOs).

Despite a disappointing learning experience with a poor lecturer, the course material itself is worth studying. The exams can be quite challenging, as the course delves into advanced finance topics and explores the 2007-2008 financial crisis. Overall, taking this course is definitely a worthwhile investment of your time.

Difficulty level: 5

Worth study: 5

FINM3008 - Portfolio Construction

Portfolio Construction draws on core investment principles, theories and techniques previously studied. The objective of this course is to introduce students to portfolio construction and asset allocation. It will focus on gaps in theory and how they can be managed in practice. Examples include challenges/realities in estimating and implementing portfolio optimisation programs, role of liquidity, and importance of plan governance. Topics will include: types of investors and their objectives; dimensions of risk; asset allocation; the nature and role of various asset classes (equity, fixed income, alternative assets, FX); building multi-manager portfolios, and implementation issues.

The course involves creating a global portfolio, which requires extensive use of Excel and various statistical methods to estimate high returns by adjusting the weight of investments in different markets. It is a challenging course, and a strong background in statistics is essential. However, I believe the Excel analysis techniques taught in this course are somewhat outdated and not as useful in today's financial world, which has seen a rapid increase in the use of machine learning and AI. Nonetheless, it is a valuable learning experience that provides a solid foundation for further studies in finance.

Difficulty level: 4

Worth study: 2

ECON1101-Microeconomics 1

The course examines how individuals and firms make decisions by weighing up costs and benefits, and how the interaction of their decisions leads to market and social outcomes. The model of market supply and demand is employed to examine the effects of taxes, subsidies, and other government interventions in market activity. The implications of different market structures, including perfect competition and monopoly, are examined. Public goods, externalities and common resources are key examples of cases in which private markets may yield socially sub-optimal outcomes. Such cases are examined and the role of government policy in correcting for these is discussed.

This economics course covers essential microeconomic concepts such as supply and demand and taxes. It is a foundational course, so it may be considered basic, but it is nonetheless important for building a solid understanding of economics. If you attend lectures regularly and review lecture slides often, the material should be relatively easy to grasp.

Difficulty level: 1

Worth study: 2-3

ECON1102-Macroeconomics 1

Macroeconomics is concerned with the operation of the economy as a whole, with attention paid to such things as unemployment, inflation, and interest rates, determination of the level of national income, savings and investment, and the exchange rate and the current account of the balance of payments. The course develops a consistent model of the economy to explore the interactions of key macroeconomic markets and variables and to examine the impacts of different kinds of shocks to the economy and the role of government budgetary and monetary policy in influencing the level of economic activity.

This economics course

Difficulty level: 1-2

Worth study: 2-3

ECON2101-Microeconomics 2

Building upon material introduced in Microeconomics 1, this course aims to provide a solid understanding of basic microeconomic theory and the ability to apply those tools and ideas. Models describing the economic behaviour of individual decision-makers and the outcomes of markets are developed and applied to examine the welfare of market participants. Questions addressed include: What influences consumer demand decisions and how? How do firms decide on how much to produce and how much inputs to use? How do prices function to coordinate economic activity? What is meant by economic efficiency? When do markets fail to achieve efficient outcomes? Training in economic analysis is achieved via weekly tutorials that go over problem sets linked to material presented in lecture. Overall, the course takes an analytical approach emphasising rigorous logical reasoning and economic problem solving.

This economics course covers some interesting material such as the AS/AD model and explores limited variations of different economic models. If you enjoy basic models with quantitative calculations, you may find it engaging. However, in my opinion, the course is quite basic and does not delve deeply into either market or monetary policy.

Difficulty level: 1-2

Worth study: 2-3

ECON2013-Behavioural Economics

This course aims to teach students some techniques of behavioural economics, classical economics, and compare the two approaches. It focuses on the principles and basic models of decision-making used by both streams of economists, as well as their consequences.

This course was a blast and the assessments were delightfully challenging. I was able to score more than 80, but it was not an easy feat. The assignments demand a solid understanding of the concepts and a strong mathematical foundation. Similarly, the exam was no walk in the park, and time management was crucial. Overall, it was an enjoyable and rewarding experience.

Difficulty level: 3-4

Worth study: 4.5

ECON2026-Money and Banking

This course has two main objectives. One is to study the role played by banks in modern monetary economies and financial markets, including issues arising from bank regulation, the role of banks in financial intermediation, and the significance of bank behaviour in monetary policy. This includes analysis of monetary innovations through crypto-currencies such as "bit-coin", and the shadow banking systems that played a significant role in the Global Financial Crisis. The second objective is to study the operation of monetary policy generally, in large economies such as the USA, and in small open economies such as Australia.

This course only provides a limited understanding of crypto-currencies and fails to explore them from a modern perspective. Instead, it focuses on the basic economic understanding of money and doesn't delve into the topic of crypto-currencies. On the positive side, the course provides valuable insights into monetary policy and global crisis, which are important concepts to learn. The exam is quite intensive and requires careful time management. It is recommended to thoroughly review all calculation and drawing questions before taking the final exam.

Difficulty level: 2-3

Worth study: 2.5

ECON2125-Optimisation for Economics and Financial Economics

Modern economic theory is based on mathematical models. Thus, a thorough understanding of the economic content of such models is not possible without a clear understanding of the mathematical concepts that underpin the modeling. This course introduces students to a range of optimisation concepts and techniques for economics and financial economics that form the basis of advanced economic theory courses. The introduced optimisation concepts and techniques will be derived from basic principles and assumptions as thoroughly as possible, and will be illustrated using standard applications from economics.

This course heavily incorporates mathematics, making it a great option for those who enjoy math and are willing to practice it. While the economic concepts covered in the course are limited, the emphasis on mathematics can be useful. However, in the context of machine learning and artificial intelligence, the mathematical focus may not be sufficient. It would be beneficial if the course could incorporate more economic concepts relevant to these fields.

Difficulty level: 3

Worth study: 1.5

ECON2141-Strategic Thinking: An introduction to Game Theory

The aim of this course is to provide an introduction to strategic thinking and analysis through the basic techniques of game theory and to illustrate the range of its applications in almost all fields of social interaction. While the level of the course will be introductory, and mathematical prerequisites are minimal, the presentation of the material will rely on precise logical arguments. This course should be of interest to students from any part of the University. Btw, this course each week has a 10% mark quiz, so if you attend the quiz on time and doing well, then you should have some fun.

This course provides a good introduction to game theory, with a focus on important concepts such as payoff matrices and decision trees. Although the course does not delve into the most complex aspects of game theory, it still challenges you to develop critical thinking skills. Personally, I found the course to be manageable and achieved a score of over 85. However, it may be more challenging for others, especially those who are not familiar with the subject matter.

Difficulty level: 3

Worth study: 3-4

EMET2007-Econometrics I: Econometric Methods

This course provides an introduction to econometric methods and their applications. The main workhorse of applied econometrics is the linear regression model and the course will develop its theory and look at a wide range of applications. The course emphasizes intuitive and conceptual understanding as well as hands on econometric analysis using modern computer software on data sets from economics and business. Students learn how to conduct empirical studies, as well as how to analyze and interpret results from other empirical works. We cover a broad range of topics, including: brief review of basic statistics; ordinary least squares estimation and its properties; choice of functional form; departures from standard OLS assumptions; time series analysis.

This course may not be the most exciting as it focuses primarily on basic regression analysis using R and does not cover more advanced statistical and machine learning concepts. However, it is an essential course for building a foundation in econometrics and is a prerequisite for more advanced courses. While it may feel outdated compared to cutting-edge ML techniques, mastering the concepts covered in this course is crucial for a strong understanding of econometric methods.

Difficulty level: 2

Worth study: 2

EMET3007-Business and Economic Forecasting

Accurate forecasting of future events and their outcomes is a crucial input into a successful business or economic planning process. This course provides an introduction to the application of various forecasting techniques. The methods include trend curve extrapolation smoothing, autoregressions, regression modelling, leading indicators. The course also looks at techniques for the evaluation of performance of forecasting methods and examines the role of forecasts in the decision making process. Students will learn how to use the various techniques in real world forecasting applications.

This course was taught by James (I think he has left now), a lecturer who has a PhD in ANU and a strong background in mathematics. The course is focused on time series analysis, and requires a deep understanding of complex mathematical formulas and their implementation in Matlab. The material is very challenging and not suitable for beginners, as it is designed for students with a strong background in mathematics. There is no final exam for this course, but students are required to complete a personal project that involves implementing a time series model. This project is very demanding and requires a high level of skill and expertise. Overall, this course is very hardcore and requires a lot of dedication and hard work. As a second-year student, I found it to be quite overwhelming and difficult to manage, but I ultimately gained a valuable understanding of time series analysis.

Difficulty level: 5

Worth study: 5

COMP1110 - Structured Programming

This course introduces students to the fundamentals of software development with a substantial group software project at its center. Major foci are data structures, object oriented programming, and an introduction to software engineering. Students will extend their understanding of software productivity tools, using revision control for group work, and be introduced to test-driven development as an integral part of software construction.

This course is an excellent introduction to the world of computer science, specifically in Java programming and Object-Oriented Programming (OOP) concepts. It covers the basics of data structures and algorithms, which are fundamental building blocks for any computer science curriculum. The group assignment is a fun and engaging project where you will work on building your own game using JavaFX as the front-end. Although the tasks may seem basic, it provides valuable practice in implementing the methods learned in class and helps solidify your understanding of OOP. Overall, this course provides a solid foundation for anyone interested in pursuing a career in computer science.

Difficulty level: 3

Worth study: 4

COMP1730 - Programming for Scientists

This course teaches introductory programming, fundamental programming language and computer science concepts, and computational problem solving illustrated with applications common in science and engineering, such as simulation and data analysis, visualisation and machine learning models. The course does not require any prior knowledge of programming, computer science or IT. There is an emphasis on designing and writing correct programs: testing and debugging are seen as integral to the programming enterprise.

I highly recommend this course as your first step into the world of computer science. The course mainly focuses on teaching you how to use Python, and it lays a solid foundation for you to use data analysis tools in your future courses. Although it doesn't cover OOP concepts, the course can be challenging or easy depending on your learning journey. It's worth noting that Python is widely used in computer science, especially in areas such as AI, ML, and DS, which many ANU CS students choose as their majors. Overall, it's a great course to help you get started in the field of computer science.

Difficulty level: 1-2

Worth study: 5

COMP2100 - Software Design Methodologies

This course continues to build on topics taught in the previous two courses. It focuses on construction of medium scale programs, using design patterns and tools that are used in the software development process. Students will gain further experience with industry standard revision control and integrated development environment (IDE) tools.

This is an advanced course in Java programming and Android development. It covers topics such as design patterns, data structures, refactoring, and patterns. The labs are excellent and provide a solid understanding of these concepts. The guidebook and tutors for this course are exceptional, the best I have ever encountered in any CECS course. The group assignment involves developing a medium-sized Android app, which is both enjoyable and provides an opportunity to work collaboratively with others while using Git. Overall, this course is highly recommended for anyone looking to become a skilled developer.

Difficulty level: 3

Worth study: 4

COMP2400 - Relational Databases

This course is an introduction to relational databases and the general skills for designing and using them. The topics include the relational data model, SQL, entity-relationship model, functional dependencies, (de-)normalisation, relational algebra, query processing and optimisation, database transactions and security. To deepen the understanding of relational databases, the current industry development of database systems such as NoSQL databases will be introduced at the end of this course.

In this course, you will learn to use the postgresql and understand the relational database concepts, which is very good and useful course for people want to do any job relates to data science and only the first assignment heavily rely on coding. The second one is more theory and not that much intensive. In all, it's very good course, choose it if it's your first semester.

Difficulty level: 2-3

Worth study: 5

COMP2620 - Logic

An introductory course in formal logic, dealing with propositional and predicate logic. Techniques of formal deduction and tests for the validity of arguments will be studied. Basic semantic concepts will be discussed.

This course serves as a prerequisite for the AI course and covers essential topics such as propositional logic and first-order logic. There are three assignments, and the second one requires programming in the Logic4fun website. Although I found this aspect a bit odd, I highly recommend this course as it is quite enjoyable, especially for those who appreciate philosophy and logical thinking. I even managed to score 28/30 for the last assignment essay, which was quite fulfilling.

Difficulty level: 2-3

Worth study: 4

COMP3425 - Data Mining

Massive amounts of data are being collected by public and private organisations, and research projects, while the Internet provides a very large source of information about almost every aspect of human life and society. Analysing such data can provide significant benefits to an organisation. This course provides a practical focus on the technology and research in the area of data mining. It focuses on the algorithms and techniques and less on the mathematical and statistical foundations.

In this course, you will learn to apply data mining techniques to real-world datasets using the rattle GUI in R. While coding in R is not required, it's still recommended to have a basic understanding of R syntax and data structures. The course assignments are mostly focused on applying models to datasets and writing reports to justify your choices. However, there have been some issues with using rattle on newer Mac silicon chips, which can cause some inconvenience. Overall, it's a valuable course for learning data mining techniques, but make sure to be prepared for potential technical issues.

Difficulty level: 3-4

Worth study: 3

COMP3620 - Artificial Intelligence

Artificial intelligence is the science that studies and develops methods of making computers more /intelligent/. The focus of this course is on core AI techniques for search, knowledge representation and reasoning, planning, and designing intelligent agents. The course also aims to give an overview of the historical, philosophical, and logical foundations of AI.

To be honest, this course is extremely challenging, especially for those who are not very confident with coding and algorithms. The workload is intense, and you need to have a solid understanding of many search algorithms. Additionally, the algorithm in KRR is extremely complex, and there are not many resources available to help you master it. One of the biggest drawbacks of the course is the lack of adequate tutoring support. The tutors' ability varies widely, and many of them are unable to help you with debugging problems. This can make the learning journey quite frustrating and discouraging, even if you attend drop-in sessions frequently. Overall, if you are up for the challenge and are willing to invest a significant amount of time and effort, you will gain valuable knowledge and skills from this course. However, be prepared for a difficult journey.

Difficulty level: 5

Worth study: 3

COMP3820 - Computing Internship

This course will enable computer science students to develop competencies expected of professionals working in business, government or the broader community. A list of available internship opportunities will be maintained for which students can apply. A holistic selection process will be used to select the best applicant for each opportunity. Students can also propose internships, but these will always be established following negotiations between the ANU and the potential host organisations, before being offered to students along with other opportunities.

This course involves finding an internship opportunity, but unfortunately, it's highly competitive. You should prepare yourself for the possibility of being rejected and not receiving any offers. The application process typically occurs in the middle of the semester, and interviews take place later on. It's not easy, as you won't know which companies will be participating or what skills they're looking for. In my experience, if a company is small and relatively unknown, and the work they do doesn't interest you, it's best to decline their offer. Doing something you're not passionate about can be a drag, and it's unlikely that they'll pay you well. However, if you do find an opportunity that aligns with your interests and skills, it can be a great experience and open up many doors for you in the future.

Competition level: 5

Worth study: 5