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Quick Facts

Medium Of Instructions	Mode Of Learning	Mode Of Delivery
English	Self Study	Video and Text Based

Course Overview

The Data Manipulation at Scale: Systems and Algorithms online course by Coursera is the first step in the Data Science at Scale Specialization series. The University of Washington offers the certification course in collaboration with Coursera.

The Data Manipulation at Scale: Systems and Algorithms online certification course aims to teach the landscape of relevant systems to the students and how these systems are evaluated along with the principles on which they rely. Students will also learn the context of data science as well as the history, skills and challenges that come while working with data. Moreover, students will get hands-on experience in learning how to structure a data science project.

Additionally, the Data Manipulation at Scale: Systems and Algorithms class programme is a self-paced learning course so that students never have to worry about missing a class. At the same time, the course is 100% online so that they can learn from the comfort of their home. The students will be awarded a shareable certificate after completing the course, which can be shared on professional platforms.

The Highlights

Flexible deadlines
Self-Paced course
100% Online
Shareable Certificate
Hands-on Project
Offered by University of Washington
Approx 20 hours to complete

Programme Offerings

online learning
Flexible Deadlines
Graded Assignments
Shareable Certificate
peer feedback
Self-paced learning
Pre-recorded course videos

Courses and Certificate Fees

Certificate Availability	Certificate Providing Authority
yes	Coursera

Data Manipulation at Scale: Systems and Algorithms

Particulars	Amount
Fee for 1 month	Rs. 4,023/-
Fee for 3 months	Rs. 8,046/-
Fee for 6 months	Rs. 12,069/-

What you will learn

Knowledge of PythonSQL knowledge

Upon completion of the Coursera Data Manipulation at Scale: Systems and Algorithms live course you will have:

Ability to describe recurring patterns, challenges, as well as approaches associated with data science projects and understanding what makes them different from projects in other related fields
Skills to use and identify programming models associated with scalable data manipulation that include relational algebra, MapReduce, and other data flow models
Knowledge to describe the landscape of specialized Big Data systems for arrays, graphs and streams
In-depth knowledge of using database technology adapted for large-scale analytics such as parallel query processing, concepts driving similar databases, and in-database analytics

Who it is for

Data AnalystData Scientist

Admission Details

To apply for the Data Manipulation at Scale: Systems and Algorithms certification programme, follow these steps:

Step 1. Visit https://www.coursera.org/

Step 2. Find ‘Data Manipulation at Scale: Systems and Algorithms online course’ on the website.

Step 3. Now, click on ‘Enroll for FREE’ option.

Step 4. Sign up to Coursera to complete the enrolment process.

Application Details

To join the Coursera Data Manipulation at Scale: Systems and Algorithms course, sign in with your Email ID and password. Opt for the desirable enrolment type to get access to the course content.

The Syllabus

Videos

Appetite Whetting: Politics
Appetite Whetting: Extreme Weather
Appetite Whetting: Digital Humanities
Appetite Whetting: Bibliometrics
Appetite Whetting: Food, Music, Public Health
Appetite Whetting: Public Health cont'd, Earthquakes, Legal
Characterizing Data Science
Characterizing Data Science, cont'd
Distinguishing Data Science from Related Topics
Four Dimensions of Data Science
Tools vs. Abstractions
Desktop Scale vs. Cloud Scale
Hackers vs. Analysts
Structs vs. Stats
Structs vs. Stats cont'd
A Fourth Paradigm of Science
Data-Intensive Science Examples
Big Data and the 3 Vs
Big Data Definitions
Big Data Sources
Course Logistics
Twitter Assignment: Getting Started

Readings

Supplementary: Three-Course Reading List
Supplementary: Resources for Learning Python
Supplementary: Class Virtual Machine
Supplementary: Github Instructions

Videos

Data Models, Terminology
From Data Models to Databases
Pre-Relational Databases
Motivating Relational Databases
Relational Databases: Key Ideas
Algebraic Optimization Overview
Relational Algebra Overview
Relational Algebra Operators: Union, Difference, Selection
Relational Algebra Operators: Projection, Cross Product
Relational Algebra Operators: Cross Product cont'd, Join
Relational Algebra Operators: Outer Join
Relational Algebra Operators: Theta-Join
From SQL to RA
Thinking in RA: Logical Query Plans
Practical SQL: Binning Timeseries
Practical SQL: Genomic Intervals
User-Defined Functions
Support for User-Defined Functions
Optimization: Physical Query Plans
Optimization: Choosing Physical Plans
Declarative Languages
Declarative Languages: More Examples
Views: Logical Data Independence
Indexes

Videos

What Does Scalable Mean?
A Sketch of Algorithmic Complexity
A Sketch of Data-Parallel Algorithms
"Pleasingly Parallel" Algorithms
More General Distributed Algorithms
MapReduce Abstraction
MapReduce Data Model
Map and Reduce Functions
MapReduce Simple Example
MapReduce Simple Example cont'd
MapReduce Example: Word Length Histogram
MapReduce Examples: Inverted Index, Join
Relational Join: Map Phase
Relational Join: Reduce Phase
Simple Social Network Analysis: Counting Friends
Matrix Multiply Overview
Matrix Multiply Illustrated
Shared Nothing Computing
MapReduce Implementation
MapReduce Phases
A Design Space for Large-Scale Data Systems
Parallel and Distributed Query Processing
Teradata Example, MR Extensions
RDBMS vs. MapReduce: Features
RDBMS vs. Hadoop: Grep
RDBMS vs. Hadoop: Select, Aggregate, Join

NoSQL Context and Roadmap
NoSQL Roundup
Relaxing Consistency Guarantees
Two-Phase Commit and Consensus Protocols
Eventual Consistency
CAP Theorem
Types of NoSQL Systems
ACID, Major Impact Systems
Memcached: Consistent Hashing
Consistent Hashing, cont'd
DynamoDB: Vector Clocks
Vector Clocks, cont'd
CouchDB Overview
CouchB Views
BigTable Overview
BigTable Implementation
HBase, Megastore
Spanner
Spanner cont'd, Google Systems
MapReduce-based Systems
Bringing Back Joins
NoSQL Rebuttal
Almost SQL: Pig
Pig Architecture and Performance
Data Model
Load, Filter, Group
Group, Distinct, Foreach, Flatten
CoGroup, Join
Join Algorithms
Skew
Other Commands
Evaluation Walkthrough
Review
Context
Spark Examples
RDDs, Benefits

Videos

Graph Overview
Structural Analysis
Degree Histograms, Structure of the Web
Connectivity and Centrality
PageRank
PageRank in more Detail
Traversal Tasks: Spanning Trees and Circuits
Traversal Tasks: Maximum Flow
Pattern Matching
Querying Edge Tables
Relational Algebra and Datalog for Graphs
Querying Hybrid Graph/Relational Data
Graph Query Example: NSA
Graph Query Example: Recursion
Evaluation of Recursive Programs
Recursive Queries in MapReduce
The End-Game Problem
Representation: Edge Table, Adjacency List
Representation: Adjacency Matrix
PageRank in MapReduce
PageRank in Pregel

Instructors

UW Washington Frequently Asked Questions (FAQ's)

1: How long will it take to complete this online Data Manipulation at Scale: Systems and Algorithms certification course?

As the course is self-paced, students can learn at their schedule, but it should take approximately 20 hours to complete it.

2: Are any additional courses available in this specialization?

Data Manipulation at Scale: Systems and Algorithms, Practical Predictive Analytics: Models and Methods, Communicating Data Science Results and Data Science at Scale - Capstone Project is four additional courses in this specialization.

3: Can I enroll for a single course from Data Science at Scale specialization?

Yes, students can enrol for a single course that interests you but taking them all in the right order will give the maximum benefit.

4: What is the benefit of taking the Data Manipulation at Scale: Systems and Algorithms training certificate experience?

Suppose you want to earn a shareable certificate and get access to the graded assignments and whole course material. In that case, you must purchase the certificate experience.

5: Is there any financial aid available?

Yes, Coursera offers financial help to students to get an experience certificate but cannot afford the fee. To know how to apply for the financial aid, refer to the ‘scholarship details’ section.