Data Science – Master Analytics and become Data Scientist
Data Science – Master Analytics and become Data Scientist
Data Science – Master Analytics and become Data Scientist
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Description
DATA SCIENCE – MASTER ANALYTICS AND BECOME DATA SCIENTIST
Neural networks, ANN, Deep learning, and other tools are available.
What you will learn.
Tools and softwares are used in data science.
There are requirements.
Basic computer knowledge is enough.
There is a description.
Data Science and Data Analytics course covers a wide range of topics.
There are 49 videos that last around 8 hours.
The section topic has a duration.
1. Data science is related to data.
Data Science introduction
What is the most powerful language?
Data science tools
There is a deep learning program.
2. There is a language called Python.
The introduction of Python.
It is recommended to install python on windows.
Understanding Python is 00:10:19.
1.5 Python coding style.
The data types are strings and numbers.
Comments and doc strings.
There are control flow statements.
Data structures are Lists and Tuples.
3.1 functions
There are 3.5 modules and packages.
3.6 Modules and Packages.
There are 4.1 Python classes.
There are 4.2 classes of inheritance.
4.3 classes are Method Resolution Order.
The file read write IO operations.
There are standard libraries.
3. R language.
R Lang’s introduction was 00:09:57.
Installation of R and R studio.
There is a language called R Language.
The language has objects factors.
2.3 R Language.
Data frames are00:1
2.5 R Language reads from and writes to files.
Control flow statements are in R Language.
Functions in the R Language.
Statistics and Probability distributions are included in the R Language.
The packages are created, build, install and package.
Plots in R Language.
DataScience and RLang are included in the Tidyverse.
The ggplot2 is 00:10:45.
Language secrets in R.
4. KNIME
The introduction is 00:04:43.
Installation and setup of KNIME.
There is a practice session for the KNIME Analytics Platform.
5. SciPY
The introduction is 00:10:24.
The introduction is 00:06:15.
A practice session with numpy.
There is a pandas-python data analysis library.
There is a practice session for the pandas.
Matplotlib introduction 00:04:38
Matplotlib has a practice session.
The IPython introduction is 00:05:06.
SymPy 00:08:24
6. Tableau
The introduction is00:11:37.
The practice session was for the public.
The practice session was for the public.
Data Science is evolving and this course will show you how to use it.
Who this course is for?
Who wants to become a data scientist?
Delivery Method
– After your purchase, you’ll see a View your orders link which goes to the Downloads page. Here, you can download all the files associated with your order.
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