4.9
7,574 条评分
★★★★★
2026年4月23日
2021年10月12日
更新内容
v7.0.4Bug fixes
应用信息
- 开发者
- SkillCat Inc
- 分类
- Education
- 价格
- 免费
- 版本
- 7.0.4
- App ID
- 1588071312
简介
Trade School? More like Trade Revolution. College is $100K of debt. Traditional trade schools are stuck in 1997. SkillCat? It’s $10/month. On your phone. And way more fun. We’re the only app where you can earn your EPA 608, OSHA-10, and Trade School Diploma while sitting on the toilet — and STILL come out certified. 300,000+ tradespeople already joined. What’s your excuse? What’s Inside: - EPA 608 & 609 Certification * Official, accredited, and fully mobile. Core. Type I, II, III. Universal. 98% pass rate. * No test center. No excuses. - Accredited Trade School Diplomas * HVAC. Plumbing. Electrical. Appliance Repair. * Self-paced. IACET-accredited. Built for people with real jobs and no time to waste. - OSHA-10 Certification * Get it. Need it. Required by just about every company that matters. - NATE Certification Prep * Want more money? Certify like a boss. NATE preps are inside the app. - 200+ Courses. No Fluff. No Filler. * From "How to not die on the job" to "Fix the unfixable." * Airflow. Wiring. Refrigerants. Motors. Diagrams. All killer, no filler. Who It’s Built For: * HVAC newbies & seasoned pros * Electricians & plumbers who want that paper * Maintenance techs leveling up * People who are done with dead-end jobs * Anyone ready to say “screw it” and build a real career Why SkillCat Slaps: * Train from your phone. Anywhere. Anytime. * No tuition. Just $10/month. Seriously. * Certs that employers actually respect * Built by real tradespeople, not some crusty board of directors * We’ll even email you memes. Maybe a photo of our CEO stress-eating drywall. SkillCat is the trade school we wish we had. It’s funny. It’s fast. It’s accredited. And it actually works. Download it. Use it. Change your life. Your future self will high-five you. Terms of Use: https://www.apple.com/legal/internet-services/itunes/dev/stdeula/
下载量预测
预估总下载量
7K
低 / 月
10K
预估 / 月
19K
高 / 月
基于评分数量 ÷ 类别评分率估算,实际下载量误差可达 ±50%,与 Sensor Tower 方法一致。
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