| |
Introduction to Julia培訓
|
| |
 班級規模及環境--熱線:4008699035 手機:15921673576( 微信同號) |
|
每期人數限3到5人。 |
| 上課時間和地點 |
開課地址：【上?！客瑵髮W(滬西)/新城金郡商務樓(11號線白銀路站)【深圳分部】：電影大廈(地鐵一號線大劇院站) 【武漢分部】：佳源大廈【成都分部】：領館區1號【沈陽分部】：沈陽理工大學【鄭州分部】：錦華大廈【石家莊分部】：瑞景大廈【北京分部】：北京中山學院 【南京分部】：金港大廈
最新開班 (連續班 、周末班、晚班）：2020年3月16日 |
| 實驗設備 |
☆資深工程師授課
☆注重質量
☆邊講邊練
☆合格學員免費推薦工作
★實驗設備請點擊這兒查看★ |
| 質量保障 |
1、培訓過程中，如有部分內容理解不透或消化不好，可免費在以后培訓班中重聽；
2、培訓結束后,授課老師留給學員聯系方式,保障培訓效果,免費提供課后技術支持。
3、培訓合格學員可享受免費推薦就業機會。 |
課程大綱 |
| |
- 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
|
|
|
|
|
|
首頁 課程表 在線聊 報名 講師 品牌 QQ聊 活動 就業