课程介绍:
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高级货,全英文,朋友从美国传过来的他们学校公开课内容,适合英文基础不错的同学来学习和理解.0 Z& s# l( K, o3 E) r
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详细目录:, g# R% e. z. O
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├─01_data-science-context-and-concepts
│ ├─01_lesson-1-examples-and-the-diversity-of-data-science
│ ├─02_lesson-2-working-definitions-of-data-science
│ ├─03_lesson-3-characterizing-this-course
│ │ 01_tools-vs-abstractions.mp4
│ │ 01_tools-vs-abstractions.srt
│ │ 02_desktop-scale-vs-cloud-scale.mp4. Y( A7 F' O; g e
│ │ 02_desktop-scale-vs-cloud-scale.srt
│ │ 03_hackers-vs-analysts.mp4
│ │ 03_hackers-vs-analysts.srt
│ │ 04_structs-vs-stats.mp4- k+ n M+ a+ A5 Q( @ H8 o
│ │ 04_structs-vs-stats.srt& v% i0 C- F |# U7 X% A. ^9 _0 D
│ │ 05_structs-vs-stats-cont-d.mp42 {7 F# @: g* l* z% x+ V ~
│ │ 05_structs-vs-stats-cont-d.srt
│ │ ( m2 @5 D" l+ t/ E, ~% E
│ ├─04_lesson-4-related-topics [- t1 H I: K4 Y, D8 s
│ │ 01_a-fourth-paradigm-of-science.mp47 {+ S, z: S' y& {! C- ?0 L' N4 k! y
│ │ 01_a-fourth-paradigm-of-science.srt
│ │ 02_data-intensive-science-examples.mp4
│ │ 02_data-intensive-science-examples.srt- n% ]. L F+ E) h2 I
│ │ 03_big-data-and-the-3-vs.mp4
│ │ 03_big-data-and-the-3-vs.srt
│ │ 04_big-data-definitions.mp4% N" X+ G& R) h1 {
│ │ 04_big-data-definitions.srt6 C6 _1 E" }$ h3 d6 ?& i
│ │ 05_big-data-sources.mp4
│ │ 05_big-data-sources.srt, O- o% F' {/ e) R2 ~2 V6 E6 n* s2 o7 ]: E
│ │ - B- h+ F; L$ u, I' r$ {
│ ├─05_lesson-5-course-logistics3 j2 X( Y: i! a) f* J
│ │ 01_course-logistics.mp4; M. P4 a4 F, F; D, d
│ │ 01_course-logistics.srt4 K# j8 m" [4 C& [
│ │ 5 i- [* A: V0 n
│ └─06_assignment-1-twitter-sentiment-analysis* |! t; D) |- P Y; K- }
├─02_relational-databases-and-the-relational-algebra
│ ├─01_lesson-6-principles-of-data-manipulation-and-management
│ ├─02_lesson-7-relational-algebra
│ ├─03_lesson-8-sql-for-data-science
│ │ 01_from-sql-to-ra.mp4
│ │ 01_from-sql-to-ra.srt% o0 _) Y0 O3 w+ o. X- s+ z0 O
│ │ 05_user-defined-functions.mp4+ { C7 k5 C) w: v- g) y. [0 @
│ │ 05_user-defined-functions.srt
│ │
│ └─04_lesson-9-key-principles-of-relational-databases
├─03_mapreduce-and-parallel-dataflow-programming% I6 \8 W+ [3 X; y8 k! y% o1 J
│ ├─01_lesson-10-reasoning-about-scale7 t; v0 Y0 {1 l( S3 h! q; p4 n9 f1 B
│ │ 01_what-does-scalable-mean.mp4. T# T6 y d0 W) b
│ │ 01_what-does-scalable-mean.srt% v3 ?' `; d' \7 s+ t8 L
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│ ├─02_lesson-11-the-mapreduce-programming-model
│ ├─03_lesson-12-algorithms-in-mapreduce
│ │ 08_mapreduce-phases.mp4& }/ W) D0 |8 ~. a/ i" e$ @
│ │ 08_mapreduce-phases.srt
│ │ ; X4 q/ |) y3 c1 r# S6 [* D( m/ k
│ └─04_lesson-13-parallel-databases-vs-mapreduce
├─04_nosql-systems-and-concepts
│ ├─01_lesson-14-what-problems-do-nosql-systems-aim-to-solve2 A' Q' |! s6 Q& c" l
│ │ 02_nosql-roundup.mp4' t+ m, X2 u$ T, j( n$ i
│ │ 02_nosql-roundup.srt/ X' Y# ]7 k3 W6 }6 w M o# _
│ │ 05_eventual-consistency.mp4: ]# [2 S9 r# a, m0 l A+ V8 ]5 X
│ │ 05_eventual-consistency.srt
│ │ 06_cap-theorem.mp4
│ │ 06_cap-theorem.srt# E1 h z) ^* I
│ │ 2 q3 H7 i7 }4 ?4 L! o
│ ├─02_lesson-15-early-key-value-systems-and-key-concepts
│ │ 01_types-of-nosql-systems.mp4
│ │ 01_types-of-nosql-systems.srt
│ │ 05_dynamodb-vector-clocks.mp4
│ │ 05_dynamodb-vector-clocks.srt' z8 e' j2 p% C
│ │ 06_vector-clocks-cont-d.mp4
│ │ 06_vector-clocks-cont-d.srt2 g& v2 |, ^# T& B
│ │
│ ├─03_lesson-16-document-stores-and-extensible-record-stores
│ │ 01_couchdb-overview.mp4( v% z5 t& O' a* C7 [; e4 K
│ │ 01_couchdb-overview.srt3 z; E. {) n) {8 }- l8 q/ r. e
│ │ 02_couchb-views.mp4$ p* k2 Z2 O% ~; s; ?6 l/ ^9 ~
│ │ 02_couchb-views.srt" ^7 E2 p& d; q* r# y# E
│ │ 03_bigtable-overview.mp4
│ │ 03_bigtable-overview.srt
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│ ├─04_lesson-17-extended-nosql-systems9 p r8 A( |/ T1 R
│ │ 01_hbase-megastore.mp4/ o, b% [3 S" i* [3 o, @
│ │ 01_hbase-megastore.srt
│ │ 02_spanner.mp4
│ │ 02_spanner.srt
│ │ 03_spanner-cont-d-google-systems.mp4
│ │ 03_spanner-cont-d-google-systems.srt
│ │ 04_mapreduce-based-systems.mp4; N) U# S# h' N2 i% q
│ │ 04_mapreduce-based-systems.srt8 R3 J) E& E1 I9 k
│ │ 05_bringing-back-joins.mp4
│ │ 05_bringing-back-joins.srt5 t: o- w& x' W" I. D4 q" @
│ │ 06_nosql-rebuttal.mp4: @3 q) w: ], q e) V( p# a$ B4 _
│ │ 06_nosql-rebuttal.srt
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│ ├─05_lesson-18-pig-programming-with-relational-algebra
│ │ 01_almost-sql-pig.mp4
│ │ 01_almost-sql-pig.srt( ^2 b6 w1 t3 k
│ │ 03_data-model.mp4# M2 ^7 P5 i$ H, t7 r0 o) s+ n1 ~
│ │ 03_data-model.srt
│ │ 04_load-filter-group.mp4
│ │ 04_load-filter-group.srt l& F( G- H, n7 L) e0 H' Q
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│ ├─06_lesson-19-pig-analytics
│ │ 01_cogroup-join.mp4( |7 m1 c5 i- @. f0 S
│ │ 01_cogroup-join.srt6 S+ B4 [8 X- H5 _, P
│ │ 02_join-algorithms.mp4
│ │ 02_join-algorithms.srt9 ^4 b7 Y4 y& K' G2 q Y& e
│ │ 03_skew.mp46 m2 V% [4 V- c: H2 h
│ │ 03_skew.srt
│ │ 04_other-commands.mp46 p( v' Z& f7 p& ^! B. L
│ │ 04_other-commands.srt
│ │ 05_evaluation-walkthrough.mp4$ {/ c: j, b. P6 u' q
│ │ 05_evaluation-walkthrough.srt' _2 u/ Q% u) q1 U
│ │ 06_review.mp4
│ │ 06_review.srt
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│ └─07_lesson-20-spark2 A0 m8 ^! v) t( o
│ 01_context.mp45 w3 d% B% t3 D% z% i4 i
│ 01_context.srt
│ 02_spark-examples.mp4! d) w0 f! v6 `+ b
│ 02_spark-examples.srt0 k% E$ T3 [ @/ v) g8 s6 _& }+ d
│ 03_rdds-benefits.mp45 Q2 O8 D% r, y9 M
│ 03_rdds-benefits.srt
│ 2 F% V9 F# k y5 G2 }
└─05_graph-analytics
├─01_lesson-21-structural-tasks; }& q( i# K) M, \* N4 i( \8 f
│ 01_graph-overview.mp4
│ 01_graph-overview.srt6 y3 J! h- Q4 b) v
│ 02_structural-analysis.mp4
│ 02_structural-analysis.srt
│ 03_degree-histograms-structure-of-the-web.mp4
│ 03_degree-histograms-structure-of-the-web.srt
│ 04_connectivity-and-centrality.mp4
│ 04_connectivity-and-centrality.srt
│ + m0 T$ Z5 @! _) y9 y, p6 ?& ^
├─02_lesson-22-traversal-tasks* F, B z/ d: |$ [6 a. q
│ 01_pagerank.mp47 C! S9 G7 o `8 `
│ 01_pagerank.srt
│ 02_pagerank-in-more-detail.mp49 C3 t/ a0 S/ \$ N0 z+ C4 y
│ 02_pagerank-in-more-detail.srt
│ 03_traversal-tasks-spanning-trees-and-circuits.mp47 S7 j8 ~% j: s$ ]
│ 03_traversal-tasks-spanning-trees-and-circuits.srt
│ 04_traversal-tasks-maximum-flow.mp4
│ 04_traversal-tasks-maximum-flow.srt
│
├─03_lesson-23-pattern-matching-tasks-and-graph-query
│ 01_pattern-matching.mp4
│ 01_pattern-matching.srt
│ 02_querying-edge-tables.mp4
│ 02_querying-edge-tables.srt
│ 05_graph-query-example-nsa.mp4
│ 05_graph-query-example-nsa.srt
│
├─04_lesson-24-recursive-queries" B* Q2 V, E; e4 _
│ 01_graph-query-example-recursion.mp4
│ 01_graph-query-example-recursion.srt
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