Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
はてなインターンのつくりかた
Search
KASUYA, Daisuke
December 18, 2016
Education
2.1k
0
Share
Embed
Copy iframe code
Copy JS code
Copy link
Start on current slide
はてなインターンのつくりかた
合同勉強会 in 大都会岡山 winter 2016の登壇資料
KASUYA, Daisuke
December 18, 2016
More Decks by KASUYA, Daisuke
See All by KASUYA, Daisuke
エンジニアリングマネージャーの成長の道筋とキャリア / Developers Summit 2025 KANSAI
daiksy
7
6.6k
はてなの開発20年史と DevOpsの歩み / DevOpsDays Tokyo 2025 Keynote
daiksy
6
4.6k
わたしがEMとして入社した「最初の100日」の過ごし方 / EMConfJp2025
daiksy
22
15k
はてなのチーム開発一巡り / Hatena Engineer Seminar 30
daiksy
0
930
ふりかえりカンファレンスLT/Get Wild
daiksy
0
2.1k
スクラムマスターの採用事情 / scrum fest fukuoka 2023
daiksy
1
3.1k
スクラムのスケールとチームトポロジー / Scaled Scrum and Team Topologies
daiksy
1
1.5k
Scrum@Scaleの理論と実装 / RSGT2022
daiksy
2
11k
リモートワークに最適なスクラムチームの人数についての仮説 / Kyoto Agile 2021
daiksy
0
310
Other Decks in Education
See All in Education
2026年度春学期 統計学 第2回 統計資料の収集と読み方 (2026. 4. 16)
akiraasano
PRO
0
170
Catecismo 26 #1 - Aula inaugural
cm_manaus
0
180
[2026前期火5] 論理学(京都大学文学部 前期 第2回)「論理的な正しさはどこにあるのか」
yatabe
0
940
Design Guidelines and Principles - Lecture 7 - Information Visualisation (4019538FNR)
signer
PRO
0
3.1k
From Participation to Outcomes
territorium
PRO
0
460
【セーフィー】テクニカルライティング&コミュニケーション実践講座(26新卒エンジニア向け研修資料)
ymzaki_m4
0
210
From Days to Minutes: How We Taught an AI to Onboard 50+ Tenants on our AI Features
mfcabrera
0
170
2026年度春学期 統計学 第3回 クロス集計と感度・特異度,データの可視化 (2026. 4. 23)
akiraasano
PRO
0
150
✅ レポート採点基準 / How Your Reports Are Assessed
yasslab
PRO
0
370
JAWS-UG初心者支部#81 GWにEduJAWSと何か作ろうもくもく会!
otsuki
0
130
We部コミュニティスライド2026-04-24
junhat6
0
180
勝手にCULTIBASE で広げよう、探究の輪! - CULTIVAL 2026
hiroc_sk
1
220
Featured
See All Featured
XXLCSS - How to scale CSS and keep your sanity
sugarenia
250
1.3M
Side Projects
sachag
455
43k
Pawsitive SEO: Lessons from My Dog (and Many Mistakes) on Thriving as a Consultant in the Age of AI
davidcarrasco
0
160
Test your architecture with Archunit
thirion
1
2.3k
The Anti-SEO Checklist Checklist. Pubcon Cyber Week
ryanjones
0
160
Leading Effective Engineering Teams in the AI Era
addyosmani
9
2k
State of Search Keynote: SEO is Dead Long Live SEO
ryanjones
0
200
Git: the NoSQL Database
bkeepers
PRO
432
67k
Accessibility Awareness
sabderemane
1
140
Site-Speed That Sticks
csswizardry
13
1.2k
Keith and Marios Guide to Fast Websites
keithpitt
413
23k
How to Ace a Technical Interview
jacobian
281
24k
Transcript
ͯͳΠϯλʔϯͷ ͭ͘Γํ 2016-12-17 ߹ಉษڧձ in େձԬࢁ - 2016 Winter -
ࣗݾհ പ୩ େี(@daiksy) ▸ גࣜձࣾ ͯͳ ▸ MackerelνʔϜαϒσΟϨΫλʔ ▸ ScalaMatsuriελοϑ
▸ ScalaؔSummitελοϑ ▸ Web+DB Press vol.96 ങ͍·͠ΐ͏ ▸ େࡕ͔Βདྷ·ͨ͠ ▸ 2012͔Βຖ͔ܽͣ͞དྷͯ·͢
ͯͳΠϯλʔϯͷͭ͘Γ͔ͨ ͯͳΠϯλʔϯͷྺ࢙
ͯͳΠϯλʔϯͷͭ͘Γ͔ͨ ͯͳΠϯλʔϯͷྺ࢙
ͯͳΠϯλʔϯͷͭ͘Γ͔ͨ ͯͳΠϯλʔϯͷྺ࢙
ͯͳΠϯλʔϯͷͭ͘Γ͔ͨ ͯͳΠϯλʔϯͷྺ࢙
ͯͳΠϯλʔϯͷͭ͘Γ͔ͨ ͯͳΠϯλʔϯͷྺ࢙
ͯͳΠϯλʔϯͷͭ͘Γ͔ͨ ͯͳΠϯλʔϯͷྺ࢙
ͯͳΠϯλʔϯͷͭ͘Γ͔ͨ ͯͳΠϯλʔϯͷྺ࢙
ͯͳΠϯλʔϯͷͭ͘Γ͔ͨ daiksyͷ͔͔ΘΓ͔ͨ ▸ 201411݄ೖࣾ ▸ 2015 Scalaߨٛͷߨࢣ ▸ 2016 ࣮ߦҕһ
▸ (εϐʔυग़ੈʂʂ)
ͯͳΠϯλʔϯͷͭ͘Γ͔ͨ ͯͳΠϯλʔϯͷܕ ▸ લ:ߨٛύʔτ ▸ ޙ:࣮ફύʔτ ▸ ޙ՝ఔνʔϜʹଐ͞Ε࣮ͯࡍͷϓϩμΫτΛ։ൃ
ͯͳΠϯλʔϯͷͭ͘Γ͔ͨ ຖਐԽͯ͠Δ ▸ ͯͳڭՊॻ(https://github.com/hatena/Hatena-Textbook) ຖΞοϓσʔτ ▸ 2015 ScalaͷߨٛΛ৽ઃ ▸ 2016
ػցֶशߨٛΛ৽ઃ
ͯͳΠϯλʔϯͷͭ͘Γ͔ͨ 2016ͷΧϦΩϡϥϜ ▸ બߟ௨ա௨ ~ ·Ͱ ▸ ࣄલ՝ ▸ https://github.com/hatena/Hatena-Intern-Exercise2016
▸ 8݄15~9݄9
ͯͳΠϯλʔϯͷͭ͘Γ͔ͨ 2016ͷΧϦΩϡϥϜ ▸ ࠓ4ίʔε ▸ ֤ίʔε2໊ͣͭ ▸ ίʔεޙͷ࣮ફύʔτͷड͚ೖΕઌͱͳΔ ▸ ͯͳϒϩάίʔε
▸ ػցֶशɾࣗવݴޠॲཧίʔε ▸ iOSΞϓϦ։ൃίʔε ▸ ΫϥυαʔόཧγεςϜίʔε (Mackerel)
ͯͳΠϯλʔϯͷͭ͘Γ͔ͨ 2016ͷΧϦΩϡϥϜ ▸ 16(Ր) ݴޠجૅ Perl or Scala ▸ 17(ਫ)
SQL/DB ▸ 18() HTTP/WebΞϓϦέʔγϣϯϑϨʔϜϫʔΫ ▸ 19(ۚ) Javascript or Swift ▸ 20() ಛผߨ࠲AWSϋϯζΦϯ
ͯͳΠϯλʔϯͷͭ͘Γ͔ͨ 2016ͷΧϦΩϡϥϜ ▸ 21() ٳΈ ▸ 22(݄) ࣗ༝՝ ▸ 23(Ր)
ػցֶश جૅฤ ▸ 24(ਫ) ػցֶश Ԡ༻ฤ ▸ 25() Πϯϑϥߨٛ
ͯͳΠϯλʔϯͷͭ͘Γ͔ͨ 2016ͷΧϦΩϡϥϜ ▸ 26(ۚ) લ՝ఔՌൃදձ ▸ 27() ژ؍ޫ ▸ 28()
ٳΈ ▸ 29(݄)~9݄8() νʔϜଐɾ࣮ફ ▸ 9(ۚ) ࠷ऴՌൃදձ
ͯͳΠϯλʔϯͷͭ͘Γ͔ͨ 2016 ࠷ऴՌ ▸ ͯͳϒϩάίʔε ▸ aboutϖʔδฤूػೳ ͳͲ ▸ ػցֶशɾࣗવݴޠॲཧίʔε
▸ Ոిձٞͷݕࡧਫ਼্ ͳͲ ▸ iOSΞϓϦ։ൃίʔε ▸ ͯͳϒϩάͷΞΫηεղੳΟδΣοτ ͳͲ ▸ ΫϥυαʔόཧγεςϜίʔε (Mackerel) ▸ ΞϥʔτάϥϑʹࢹઃఆͷᮢΛඳը ͳͲ
ͯͳΠϯλʔϯͷͭ͘Γ͔ͨ ௨শʰਫ਼ਆͱ࣌ͷ෦ʱ
ͯͳΠϯλʔϯͷͭ͘Γ͔ͨ Πϯλʔϯͷత ▸ ࠾༻؍ ▸ ֶੜͱاۀ͕ೱີʹίϛϡχέʔγϣϯͰ͖Δػձ ▸ ࣾڭҭ؍ ▸ ڭՊॻࣾͷڭҭʹ͑Δ
▸ एखΤϯδχΞʹߨࢣ/ϝϯλʔΛܦݧͤ͞Δ ▸ ࣾձߩݙ؍ ▸ ΠϯλʔωοτͷԸฦ͠
ͯͳΠϯλʔϯͷͭ͘Γ͔ͨ Πϯλʔϯͷ४උ ▸ 3݄15 ΠϯλʔϯҕһձΩοΫΦϑ ▸ 3݄ ΧϦΩϡϥϜͷ͓͓ΑͦΛܾΊΔ ▸ ίϯϐϡʔλɾαΠΤϯεͷߨٛΛՃ͍ͨ͠ɺͱ͍͏͘
Β͍ͷΞότͳߏ ▸ Alpha Go͕ྲྀߦͬͯͨͷͰAlphaޒฒ࣮͠Α͏ͱ͔ ݴͬͯͨ ▸ ࠷ऴతʹ͜Ε͕৽ઃͷػցֶशߨٛͱ࣮ͯ͠ݱ͢Δ
ͯͳΠϯλʔϯͷͭ͘Γ͔ͨ Πϯλʔϯͷ४උ ▸ 4݄ ։࠵ࠂͱࣄલొ։࢝ ▸ 5݄ ืूαΠτͷ࡞ɻ25ʹืूαΠτΦʔϓϯ ▸ 6݄
ߨٛϓϩάϥϜͷৄࡉ͕ϑΟοΫεɻߨࢣͷબఆͳͲ ▸ 7݄ ืूకΊΓɻߨٛ४උɻڭՊॻͷΞοϓσʔτɻબߟ ͱ݁Ռ࿈བྷɻ ▸ 8݄ ຊ൪։࢝
ͯͳΠϯλʔϯͷͭ͘Γ͔ͨ Πϯλʔϯʹ͔͔ΘΔਓʑ ▸ ΤϯδχΞ৬ ▸ Πϯλʔϯҕһձ 4໊ ▸ ߨࢣ 11໊
▸ ϝϯλʔ 7໊ ▸ ͦͷଞͷ৬छ ▸ ਓࣄ 2໊ ▸ σβΠφ 1໊ ▸ ͦͷଞ ฤू, ใ ͳͲ
ͯͳΠϯλʔϯͷͭ͘Γ͔ͨ Πϯλʔϯͷ४උظؒͷʹ͍ͭͯ ▸ ֤νʔϜσΟϨΫλ͔Βɺिͷ10%΄ͲͷΛׂ͔ͤͯ Β͏Α͏ґཔ ▸ ʮઐ৬10%ϧʔϧʯΛ׆༻
ͯͳΠϯλʔϯͷͭ͘Γ͔ͨ ͭΒ͔ͬͨ͜ͱ ▸ ਘৗͰͳ͍ϓϨογϟʔ ▸ ʮͯͳΠϯλʔϯʯͱ͍͏ϒϥϯυ ▸ ୭Ԡืͯ͘͠Εͳ͔ͬͨΒͲ͏͠Α͏… ▸ ͍͍ਓ͕དྷͳ͔ͬͨΒͲ͏͠Α͏…
▸ ίϯτϩʔϥϒϧͰͳ͍ཁૉଟ͍
ͯͳΠϯλʔϯͷͭ͘Γ͔ͨ ͭΒ͔ͬͨ͜ͱ ▸ બߟ͕େม ▸ ݁Ռతʹաڈ࠷ଟͷԠื ▸ ͜ͷਓ͔ΒͲ͏ͬͯ8໊બ… ▸ ௨ա࿈བྷޙʹࣙୀ͕͋ͬͨΓ
ͯͳΠϯλʔϯͷͭ͘Γ͔ͨ ͭΒ͔ͬͨ͜ͱ ▸ ࣾௐ͕େม ▸ ͯͳͷશ৬छ͕ͳΜΒ͔ͷܗͰ͔͔Θͬͯ͘ΕΔ ▸ શһΊͪΌͪ͘Όલ͖ʹखͬͯ͘ΕΔ ▸ ͱ͍͑ਓؔ࿈෦͕ଟ͍͗ͯͨ͢Μ
▸ ڞ༗࿙ΕͳͲҕһձͱͯ͠ͷল͕͍͔ͭ͘
ͯͳΠϯλʔϯͷͭ͘Γ͔ͨ ՝ ▸ ΠϯλʔϯࠓͲͬͯ͜Δ ▸ Նͩͱଟ͘ͷձࣾͱ࣌ظ͕ඃΔ ▸ ֶੜෳͷΠϯλʔϯʹߦ͘ ▸ Πϯλʔϯͷ௨Խ/ظؒԽ
▸ ͯͳΠϯλʔϯ৽͍͠ܕΛߟ͑Δ࣌ظͩͱײ͡Δ
ͯͳΠϯλʔϯͷͭ͘Γ͔ͨ Πϯλʔϯͷࣄ͍ͭ·Ͱʁ ▸ ࣮·ͩऴΘͬͯͳ͍ɻϨϙʔταΠτ࡞ͬͯΔ ▸ དྷͷҕһձʹҾ͖ܧ͗͢Δ·Ͱ͕ҕһͷ͠͝ͱ
ͯͳΠϯλʔϯͷͭ͘Γ͔ͨ ΤϯδχΞઈࢍืूதʂ ▸ ৽ଔ ▸ த్ ▸ དྷͷΠϯλʔϯੜ ▸ ͓ؾܰʹ͓͕͚͍ͩ͘͞ʂʂʂ
ͯͳΠϯλʔϯͷͭ͘Γ͔ͨ ͝ਗ਼ௌ͋Γ͕ͱ͏͍͟͝·ͨ͠