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Introduction to Julia培训
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 班级规模及环境--热线:4008699035 手机:15921673576/13918613812( 微信同号) |
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坚持小班授课，为保证培训效果，增加互动环节，每期人数限3到5人。 |
| 上课时间和地点 |
开课地址：【上海】同济大学(沪西)/新城金郡商务楼(11号线白银路站)【深圳分部】：电影大厦(地铁一号线大剧院站) 【武汉分部】：佳源大厦【成都分部】：领馆区1号【沈阳分部】：沈阳理工大学【郑州分部】：锦华大厦【石家庄分部】：瑞景大厦【北京分部】：北京中山 【南京分部】：金港大厦
新开班 (连续班 、周末班、晚班）：即将开课，详情请咨询客服。(欢迎您垂询，视教育质量为生命！) |
| 实验设备 |
☆资深工程师授课
☆注重质量
☆边讲边练
☆合格学员免费推荐工作
★实验设备请点击这儿查看★ |
| 质量保障 |
1、培训过程中，如有部分内容理解不透或消化不好，可免费在以后培训班中重听；
2、课程完成后,授课老师留给学员手机和Email,保障培训效果,免费提供半年的技术支持。
3、培训合格学员可享受免费推荐就业机会。 |
课程大纲 |
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- Introduction to Julia
What niche is filled by Julia
How can Julia help you with data analysis
What you can expect to get out of this course
Getting started with Julia's REPL
Alternative environments for Julia development: Juno, IJulia and Sublime-IJulia
The Julia ecosystem: documentation and package search
Getting more help: Julia forums and Julia community
Strings: Hello World
Introduction to Julia REPL and batch execution via "Hello World"
Julia String Types
Scalar Types
What is a variable? Why do we use a name and a type for it?
Integers
Floating point numbers
Complex numbers
Rational numbers
Arrays
Vectors
Matrices
Multi-dimensional arrays
Heterogeneous arrays (cell arrays)
Comprehensions
Other Elementary Types
Tuples
Ranges
Dictionaries
Symbols
Building Your Own Types
Abstract types
Composite types
Parametric composite types
Functions
How to define a function in Julia
Julia functions as methods operating on types
Multiple dispatch
How multiple dispatch differs from traditional object-oriented programming
Parametric functions
Functions changing their input
Anonymous functions
Optional function arguments
Required function arguments
Constructors
Inner constructors
Outer constructors
Control Flow
Compound expressions and scoping
Conditional evaluation
Loops
Exception Handling
Tasks
Code Organization
Modules
Packages
Metaprogramming
Symbols
Expressions
Quoting
Internal representation
Parsing
Evaluation
Interpolation
Reading and Writing Data
Filesystem
Data I/O
Lower Level Data I/O
Dataframes
Distributions and Statistics
Defining distributions
Interface for evaluating and sampling from distributions
Mean, variance and covariance
Hypothesis testing
Generalized linear models: a linear regression example
Plotting
Plotting packages: Gadfly, Winston, Gaston, PyPlot, Plotly, Vega
Introduction to Gadfly
Interact and Gadfly
Parallel Computing
Introduction to Julia's message passing implementation
Remote calling and fetching
Parallel map (pmap)
Parallel for
Scheduling via tasks
Distributed arrays
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