Tags
Language
Tags
August 2025
Su Mo Tu We Th Fr Sa
27 28 29 30 31 1 2
3 4 5 6 7 8 9
10 11 12 13 14 15 16
17 18 19 20 21 22 23
24 25 26 27 28 29 30
31 1 2 3 4 5 6
    Attention❗ To save your time, in order to download anything on this site, you must be registered 👉 HERE. If you do not have a registration yet, it is better to do it right away. ✌

    ( • )( • ) ( ͡⚆ ͜ʖ ͡⚆ ) (‿ˠ‿)
    SpicyMags.xyz

    Coursera - Introduction to Data Science (University of Washington)

    Posted By: ParRus
    Coursera - Introduction to Data Science (University of Washington)

    Coursera - Introduction to Data Science (University of Washington)
    WEBRip | English | MP4 + PDF Slides | 960 x 540 | AVC ~69.9 kbps | 30 fps
    AAC | 117 Kbps | 44.1 KHz | 2 channels | Subs: English (.srt) | ~17 hours | 1.36 GB
    Genre: eLearning Video / Computer Science, Programming

    Commerce and research are being transformed by data-driven discovery and prediction. Skills required for data analytics at massive levels – scalable data management on and off the cloud, parallel algorithms, statistical modeling, and proficiency with a complex ecosystem of tools and platforms – span a variety of disciplines and are not easy to obtain through conventional curricula. Tour the basic techniques of data science, including both SQL and NoSQL solutions for massive data management (e.g., MapReduce and contemporaries), algorithms for data mining (e.g., clustering and association rule mining), and basic statistical modeling (e.g., linear and non-linear regression).
    Syllabus
    Part 0: Introduction
    Examples, data science articulated, history and context, technology landscape
    Part 1: Data Manipulation at Scale
    Databases and the relational algebra
    Parallel databases, parallel query processing, in-database analytics
    MapReduce, Hadoop, relationship to databases, algorithms, extensions, languages
    Key-value stores and NoSQL; tradeoffs of SQL and NoSQL
    Part 2: Analytics
    Topics in statistical modeling: basic concepts, experiment design, pitfalls
    Topics in machine learning: supervised learning (rules, trees, forests, nearest neighbor, regression), optimization (gradient descent and variants), unsupervised learning
    Part 3: Communicating Results
    Visualization, data products, visual data analytics
    Provenance, privacy, ethics, governance
    Part 4: Special Topics
    Graph Analytics: structure, traversals, analytics, PageRank, community detection, recursive queries, semantic web
    Guest Lectures
    Taught by Bill Howe

    also You can watch my other helpful: Coursera-posts
    (if old file-links don't show activity, try copy-paste them to the address bar)

    General
    Complete name : 09_Parallel_Databases_16-18.mp4
    Format : MPEG-4
    Format profile : Base Media
    Codec ID : isom (isom/iso2/avc1/mp41)
    File size : 22.7 MiB
    Duration : 16 min 18 s
    Overall bit rate mode : Variable
    Overall bit rate : 194 kb/s
    Encoded date : UTC 1970-01-01 00:00:00
    Tagged date : UTC 1970-01-01 00:00:00
    Writing application : Lavf53.29.100

    Video
    ID : 1
    Format : AVC
    Format/Info : Advanced Video Codec
    Format profile : High@L3.1
    Format settings : CABAC / 4 Ref Frames
    Format settings, CABAC : Yes
    Format settings, RefFrames : 4 frames
    Codec ID : avc1
    Codec ID/Info : Advanced Video Coding
    Duration : 16 min 18 s
    Bit rate : 69.9 kb/s
    Width : 960 pixels
    Height : 540 pixels
    Display aspect ratio : 16:9
    Frame rate mode : Constant
    Frame rate : 30.000 FPS
    Color space : YUV
    Chroma subsampling : 4:2:0
    Bit depth : 8 bits
    Scan type : Progressive
    Bits/(Pixel*Frame) : 0.004
    Stream size : 8.15 MiB (36%)
    Writing library : x264 core 120 r2120 0c7dab9
    Encoding settings : cabac=1 / ref=3 / deblock=1:0:0 / analyse=0x3:0x113 / me=hex / subme=7 / psy=1 / psy_rd=1.00:0.00 / mixed_ref=1 / me_range=16 / chroma_me=1 / trellis=1 / 8x8dct=1 / cqm=0 / deadzone=21,11 / fast_pskip=1 / chroma_qp_offset=-2 / threads=12 / sliced_threads=0 / nr=0 / decimate=1 / interlaced=0 / bluray_compat=0 / constrained_intra=0 / bframes=3 / b_pyramid=2 / b_adapt=1 / b_bias=0 / direct=1 / weightb=1 / open_gop=0 / weightp=2 / keyint=250 / keyint_min=25 / scenecut=40 / intra_refresh=0 / rc_lookahead=40 / rc=crf / mbtree=1 / crf=28.0 / qcomp=0.60 / qpmin=0 / qpmax=69 / qpstep=4 / ip_ratio=1.40 / aq=1:1.00
    Encoded date : UTC 1970-01-01 00:00:00
    Tagged date : UTC 1970-01-01 00:00:00

    Audio
    ID : 2
    Format : AAC
    Format/Info : Advanced Audio Codec
    Format profile : LC
    Codec ID : mp4a-40-2
    Duration : 16 min 18 s
    Bit rate mode : Variable
    Bit rate : 117 kb/s
    Maximum bit rate : 128 kb/s
    Channel(s) : 2 channels
    Channel positions : Front: L R
    Sampling rate : 44.1 kHz
    Frame rate : 43.066 FPS (1024 SPF)
    Compression mode : Lossy
    Stream size : 13.6 MiB (60%)
    Default : Yes
    Alternate group : 1
    Encoded date : UTC 1970-01-01 00:00:00
    Tagged date : UTC 1970-01-01 00:00:00

    Screenshots

    Coursera - Introduction to Data Science (University of Washington)

    Coursera - Introduction to Data Science (University of Washington)

    Coursera - Introduction to Data Science (University of Washington)

    Coursera - Introduction to Data Science (University of Washington)

    Coursera - Introduction to Data Science (University of Washington)

    ✅ Exclusive eLearning Videos ParRus-blogadd to bookmarks

    Feel free to contact me PM
    when links are dead or want any repost

    Coursera - Introduction to Data Science (University of Washington)