Programming Language Practice Exams

Yes, the choice depends heavily on what you want to build. For data science, AI/ML, automation, and general-purpose programming, Python is the right starting point — it's #1 in the TIOBE Index (around 20% share in May 2026), has the most beginner-friendly syntax, dominates AI/ML work, and is in highest demand in current hiring. For systems programming, embedded development, operating systems, or game engines, C and C++ remain the right choices — C is #2 in TIOBE (around 11.5%), C++ is #4 (around 8.7%, with Java having edged past it in May 2026), and both anchor performance-critical work that AI tooling cannot easily replace.

For Windows desktop applications, especially in healthcare/medical, point-of-sale, accounting, scientific/industrial software, and many legacy enterprise systems, Delphi (Object Pascal) sits at #10 in TIOBE and remains an underserved high-paying niche. For enterprise business applications, Java (#3 in May 2026) and C# (#5) are strong choices. The honest framing: there's no "best" language — there's the language that matches the work you want to do. Most professional developers eventually learn 3–5 languages over their career.

A computer science degree teaches you computer science (algorithms, data structures, theory of computation, systems design, math) using one or two teaching languages — typically Python, Java, or C/C++ in 2026. Learning a programming language teaches you the language itself plus enough surrounding tooling to build things. The two aren't substitutes: a CS degree without language fluency leaves you unable to build working software; language fluency without CS foundations leaves you unable to design systems beyond a certain complexity.

The realistic 2026 framing: for most working developer roles (web development, application development, automation, junior data engineering, junior ML engineering), language fluency plus a portfolio of working projects gets you hired without a CS degree. For roles requiring systems-level depth (compilers, operating systems, distributed systems infrastructure, ML research, security research, embedded systems engineering at scale), CS foundations matter more than language choice. Total cost: learning Python well takes 6–12 months of focused effort with $0–$500 in resources; a CS degree takes 4 years and $40K–$200K. Pragmatic path: learn languages and build a portfolio first, pursue formal CS education later if specific roles require it.

Language choice meaningfully affects salary, though experience and role specialization matter more. US developer salary bands by primary language as of 2026 (Stack Overflow Developer Survey, ZipRecruiter, Glassdoor, Levels.fyi aggregates — treat as direction, not promise): Python $90K–$140K with senior ML/AI engineers reaching $180K–$300K+ in top-tier companies; C/C++ $95K–$160K with senior systems and embedded engineers $150K–$220K+ (particularly in defense, semiconductors, autonomous vehicles, and high-frequency trading); Java $90K–$140K with senior enterprise engineers $140K–$180K; C# $85K–$130K with senior Microsoft-ecosystem engineers $130K–$170K.

Delphi/Object Pascal developers $86K–$140K (ZipRecruiter median around $108K, Glassdoor average around $102K) with senior developers reaching $153K–$181K — Delphi salaries are unusually concentrated at the top because demand exceeds supply in maintaining legacy systems. JavaScript/TypeScript $85K–$135K for general web work, with senior full-stack engineers higher. Salary varies less by language than by industry vertical (defense > finance > general enterprise > startup) and by years of experience.

For most developers in 2026, yes — but with important nuance. Python's position is unusual: AI tooling (GitHub Copilot, Cursor, Claude Code, similar AI coding assistants) is trained heavily on Python and produces particularly good Python code, which simultaneously makes Python the easiest language for AI to write AND the language where AI most threatens entry-level developer work. The Python work most exposed to AI displacement is rote scripting, basic data manipulation, and simple web backends.

The Python work most insulated from AI displacement is ML/AI engineering itself (building the models AI tooling depends on), production data engineering at scale, complex systems design, and the judgment work of architecting Python applications that handle real business complexity. The honest 2026 framing: Python remains a strong choice if you're targeting AI/ML, data engineering, or research roles. For pure software development careers, pair Python with at least one lower-level language (C++ or Rust) for systems work, or one strongly-typed language (Java, C#, Go) for enterprise work. Python alone is increasingly insufficient for senior developer careers; Python plus complementary languages is the strongest combination.

Because C and C++ dominate work Python fundamentally cannot do well. C is the closest practical language to the hardware — operating systems (Linux, Windows, macOS kernels are all C-based), embedded systems (every microcontroller in your car, appliances, medical devices), real-time systems, and the runtimes underneath higher-level languages including Python itself. C++ extends C with object-oriented features and dominates game engines (Unreal Engine), high-frequency trading systems, autonomous vehicle software, computer graphics, scientific computing, large-scale database internals (PostgreSQL, MySQL), and any application where performance and memory control matter more than developer convenience.

Both languages remain at the top of TIOBE in 2026 — C at #2, C++ at #4 — because AI workloads themselves are increasingly built on C++ (PyTorch, TensorFlow internals are largely C++; CUDA kernels are C++; the GPU compute infrastructure powering AI is C++ from the ground up). C and C++ are also among the most AI-resistant languages because the work requires precise judgment about memory, performance, and undefined behavior that AI tooling struggles with. Senior C/C++ developers in defense, semiconductors, autonomous vehicles, and HFT routinely earn $180K–$300K+. The trade-off: longer learning curve and more time investment than Python.

Delphi is meaningfully alive, and it's one of the most underrated career niches in software in 2026. Embarcadero (which acquired the Delphi tooling from Borland via CodeGear in 2008 for ~$24.5M, and was itself acquired by Idera Software in October 2015) actively maintains Delphi RAD Studio with regular releases — Delphi 12 Athens shipped in November 2023, Delphi 12.3 Athens shipped March 2025 with a 64-bit IDE and Android 15 support, and RAD Studio 13 "Florence" released September 2025 added AI components and an AI companion. TIOBE consistently ranks Delphi/Object Pascal in the top 10 (anchored at #10 in May 2026).

The career angle is unusual: Delphi's demand is concentrated in maintaining and extending mission-critical Windows desktop applications written between 1995–2010 — and there are millions of these applications still running in healthcare (medical practice management, EHR add-ons), point-of-sale, accounting/financial software, scientific/industrial control systems, and small-to-medium business ERP. The supply of Delphi developers is shrinking (older developers retiring) while demand persists (companies cannot easily rewrite mission-critical Delphi codebases). Result: Delphi developer salaries are unusually concentrated at the top of the band — ZipRecruiter US median around $108K, 75th percentile $140K, top earners $153K–$181K. Delphi Community Edition is free for personal/non-commercial use (up to $5,000 in annual revenue), making it zero-cost to start learning.

Yes, regularly — particularly for languages with strong open-source ecosystems and demonstrable portfolio work. The realistic degree-free path: pick one primary language (Python, JavaScript, C#, or Delphi are particularly degree-tolerant), build a public GitHub portfolio with 5–10 substantive projects that solve real problems (not tutorials), contribute to one or two open-source projects, complete a relevant vendor certification (AWS Cloud Practitioner, Microsoft AZ-900, Python Institute PCEP/PCAP, or similar — every vendor sheet in this workbook covers these in detail), and apply to companies known for skills-based hiring.

Companies actively hiring without degree requirements in 2026 include most startups, many mid-size tech companies, the AWS/Azure/Google Cloud partner ecosystems, and large employers that have explicitly relaxed degree requirements (IBM, Google, Apple, Bank of America, and others have all publicly announced or operationalized skills-first hiring for many engineering roles). The honest caveat: degree-free paths work best for application development, web development, automation, and most cloud/DevOps work. They work less well for ML research, security research, embedded systems engineering at top firms, and traditional Fortune 100 companies with rigid HR filters. Pairing language fluency with a portfolio AND a vendor certification is more powerful than any single credential alone.

For certifications, many vendor-neutral programming credentials have historically been on the VA-approved licensing-and-certification list — Python Institute (PCEP/PCAP/PCPP), Oracle Certified Professional Java SE, Microsoft language-related certs, Linux Foundation certs, and many others — with reimbursement applying whether you pass or fail (submit VA Form 22-0803 after the exam). Confirm the specific exam is currently approved at va.gov before relying on reimbursement, since the VA's approved-tests list is updated periodically.

Veterans have several strong free or low-cost paths to language fluency: Microsoft Software & Systems Academy (MSSA) provides free training during transition for service members on active duty within 180 days of separation; AWS re/Start covers Python, Linux, and cloud languages; Google Career Certificates (offered free to veterans through Coursera and Grow with Google for Veterans) cover Python and other languages; the Department of Labor's Apprenticeship.gov platform lists hundreds of registered software developer apprenticeships including language-specific tracks. For Delphi specifically, Embarcadero offers free Community Edition licenses for personal/non-commercial use — veterans interested in Delphi can build full hands-on competence at zero cost. Veterans transitioning from any role with technical or analytical work (intelligence, signals, military IT, cybersecurity) often find Python particularly natural as a civilian translation language.

Pairing language fluency with vendor certifications is the strongest career strategy in 2026 — and the right language depends on your target vendor track. For AWS, Azure, or Google Cloud careers: Python is the strongest pairing (AWS Lambda, Azure Functions, and Google Cloud Functions all run Python natively; infrastructure-as-code with Terraform or AWS CDK frequently uses Python; cloud automation is Python-heavy). For Databricks: Python plus SQL — Databricks notebooks are predominantly PySpark and SQL. For Salesforce: Apex (Salesforce's proprietary Java-like language) plus JavaScript for Lightning Web Components.

For Microsoft enterprise: C# is the natural pairing. For Oracle Database: SQL plus PL/SQL. For SAP: ABAP is the developer pairing. For Cisco DevNet/automation: Python dominates. For cybersecurity careers (CompTIA Security+ path): Python plus PowerShell plus enough Bash to navigate Linux. For Pega: Pega's low-code platform reduces language importance, but Java background helps with extensions. For embedded/IoT/defense careers (Azure IoT, AWS IoT): C and C++ remain essential.