The cultivation of certain abilities doesn’t require a great deal of investment, if any. You can often improvise with the little equipment already at your disposal to train just enough of a certain ability to proceed to the next level. At that point you can determine if further pursuit warrants financial investment. I’m fairly pedantic in making even a minimal investment in an enterprise until fair certainty of progress and saturation of available resources. Beyond that, I find the exercise of creativity in harnessing existing resources a rewarding experience in it’s own right.
I consider the above approach lazy learning, although I overloaded the term in presence of a series of alternate definitions likely in existence.
Optional trivia: In Machine Learning, lazy learners are those just-in-time learning classifiers that experience a low cost to train the model with a new data point, but a higher-cost classification op for a query point. A K-Nearest-Neighbor classifier is one example of a lazy learner. A linear regression classifier is the opposite - an eager learner. It experiences a higher cost to retrain the model with a new data point, but a low cost to classify an element.
What activities lend themselves to lazy learning? I should mention that the following list somewhat overlaps with the respective Pareto principle list since lazy-learning resource simplification shares a common philosophy with minimizing the process to achieve the majority of the desired outcome.
Prerequisites: pen and paper.
Develop publishable content first, ideally in a few categories you wish to dedicate yourself to. Then spend some minimal effort to launch a site using some readily available template in WordPress or other free hosting platform. Don’t worry yet about a paid plan or a catchy domain until you produce enough content and attract some readers.
Prerequisites: any recording device or phone.
Discover and strengthen your style before investing in additional equipment. No quality equipment can mask flaws in confidence, presentation, or material coherency, which is why it would behoove you to abstract this aspect from the more expensive infrastructure.
Prerequisites: any functional video camera, including phone.
Improvise a setting and find a way to mount the device on some stable surface or recruit a ‘camera assistant.’ Alternatively, sustain the camera in your hand, in spite of the overall bad practice. Proceed with filming and continue until having sufficiently developed camera presence.
Bonus: a towel, a chair, a pull-up bar or surface.
Everything you need to cultivate a sustainable fitness habit lies around you. A chair helps for some peculiar abdominal exercises or to add resistance for certain elevated movements. Find a pull-up bar or some ledge to hang on and perform pull-ups. Most fundamental exercises you can perform on the ground indoors or outdoors. Gym equipment is necessary if you 1) develop consistency 2) decide to pursue a heavier workout focused on brute strength or weight gain, or 3) decide, after a trial, that you prefer a more social setting.
Prerequisites: any athletic shoes.
Before investing in expensive shoe-ware or other apparel, perform a series of trial runs to gauge your interest. A few weeks of gradual running in inferior shoe-ware will not compromise your joints, at least not with that as the root cause.
Prerequisites: pen, paper.
Find an online tutorial and proceed. Drawabox is one I found quiet effective.
Prerequisites: open-source software, free tutorials.
Use Gimp if you prefer a fully-featured graphical toolkit, Inkscape for vector graphics, or Asymptote for a programmable vector graphics interpreted language approach. The online Tinkercad provides a digital design SaaS (software as a service) approach. Acquire free learning resources from YouTube, Coursera, Udacity, etc.
Prerequisites: open-source free simulators.
You can gain impressive knowledge by experimenting with simulators without access to physical electronics equipment. Use the NGSPICE circuit simulator for a programmable approach or something like XCircuit for a graphical front-end. Tinkercad, in addition to digital design, now offers an electronics toolkit, providing not only basic analog components, but also digital such as Arduino boards that you can simulate online. You can save your projects along with the necessary code, as well as share with the open community. I find access to these SaaS tools incredible, although somewhat computationally demanding to simulate on less powerful hardware.
Alternatively, if you desire access to a physical community and hardware, you could join a makerspace if one is available in your area. These are also called hackerspaces. See this wiki for a not necessarily complete list. Some feature a modest monthly membership, while some are free of charge. These spaces provide access to tons of hardware and electronics components to experiment with, not to mention the collaborative aspect with other members.
Some makerspaces provide access to wood working, soldering, metal cutting, laser cutting, and 3d printing equipment. Investigate what’s available around you. A monthly membership could prove a cost effective option to learn, experiment, and collaborate.
Prerequisites: YouTube, online lessons, free introductory group lessons, social events.
You can gauge personal interest and willingness to pursue a particular dance without much spending. YouTube is saturated with videos, lessons, and tutorials. Use these to acquire basic abilities. You will inevitably need to practice as the only means to solidify your skills. Maybe you already have a dance partner at your disposal. Alternatively, tame your fear and head to a club or local dancing event. You can carry this process a long way without hardly any spending.
Prerequisites: free online resources.
Given your interest in the broader Computer Science discipline, you need not invest in a university education or even paid online coursework or textbooks - at least not until sometime in the future once you’ve asserted your pursuit.
What does Computer Science entail in the most basic of components?
Programming, with a certain exposure to modular, functional, or object-oriented paradigms.
Computer Science originates from applied mathematics, and you cannot consider yourself a computer scientist without an algorithmic mindset and the ability to analyze algorithms for computational or space complexity. Additionally, you will have gained the ability to categorize and map certain problems to a specific class of algorithms with known properties, which allows you to focus on unique aspects of your problem rather than (unintelligently) constructing the entire system from scratch. Algorithmic maturity forms an integral component of Computer Science education. This implies certain prerequisites in discreet mathematics and probability, but you can often obtain missing knowledge in parallel.
Your concentration of interest.
For more involved software design, seek the respective online resources. For an overall exposure to computer architecture from first principles, see the nand2tetris free course. It covers the entire stack from the basic digital logic components to the compiler and OS level, in one impressive, highly interactive offering. For other specialties including networks, security, Human Computer Interaction, and Databases, plenty of specific coursework exists on Coursera, Udacity, or MIT OCW. The same applies to Artificial Intelligence or Machine Learning. See the Andrew NG course, for example. You could ultimately gain significant momentum in becoming a field Computer scientist by intelligently yet actively pursuing the minimal relevant curriculum and eliminating the unessentials.
Prerequisites: modest spending and some creativity.
Provided you don’t have access to a computing device to carry out any of the above or your own independent projects, you can improvise a device for under US $100 in many cases. I assume you wish to use the device to learn and create, and not for gaming or rich multimedia experiences, in which case you probably would not be reading this.
If you are not adverse to some Linux variant OS, you can purchase a Raspberry PI board for under US $40, providing you with all the basic computation necessary to program, watch instructional video content, and interact with software not too computationally demanding. The remaining apparel necessary to interact with the board, including the keyboard/mouse, SD card, and some basic monitor, you could probably obtain for under US $60, especially refurbished or used, or possibly new. I’ve seen touch screen displays sold very inexpensively for specific usage with a Raspberry PI.
For more computationally demanding applications, you can find entire desktops sold from independent Asian manufacturers for under US $80. This option could facilitate all your computational demands, although you would still need access to additional I/O and display devices.
For occasional but infrequent need to demanding computation, you could use inexpensive hardware to learn/develop/create, and ‘outsource’ intense computation to an online IaaS (infrastructure as a service) platform such as Amazon EC2 or Digital Ocean. Both of these cloud computing platforms offer introductory user or educational discounts, although the general cost can be tiny with intelligent usage.
The key component involves the ability to abstract the different operations in your workflow, as each abstracted layer often experiences varying infrastructural demand.
With total lack of personal hardware, alternative measures involve the yet again mentioned makerspaces (which occasionally provide access to computing devices), university labs, or a local library.