This diploma is the ideal scientific and practical choice for your excellence in data science.
This diploma is a combination of technical skills from both business sciences and technology to build a career future in one of the most important fields worldwide; where the most of global and innovative companies are utilizing data science to help making data-driven decisions after developing statistical models and algorithms
Full knowledge of Data Analysis skills using Microsoft Excel and the business intelligence using Microsoft Power BI.
Besides rounds that are conducted in IMP head office in Egypt; IMP courses are also delivered LIVE with fully interactive sessions allowing for a highly engaging Q & A and assuring that you get the best ever learning experience.
Start Date | Time | Days | Delivery Type |
4-Sep | 5:00 PM – 9:00 PM | Saturday | Interactive Classroom Training |
To have successfully completed; a trainee should:
Lecture 3.1
Basic Statistics: Cases, Variables, Types of Variables
Lecture 3.2
Basic Statistics : Matrix and Frequency Table
Lecture 3.3
Basic Statistics : Graphs and Shapes of Distributions
Lecture 3.4
Basic Statistics : Mode, Median and Mean
Lecture 3.5
Basic Statistics : Range, Interquartile Range and Box Plot
Lecture 3.6
Basic Statistics : Variance and Standard deviation
Lecture 3.7
Basic Statistics : Basics of Regression Probability
Lecture 3.8
Probability : Elementary Probability
Lecture 3.9
Probability : Random Variables and Probability Distributions
Lecture 3.10
Probability : Normal Distribution, Binomial Distribution & Poisson Distribution
Lecture 3.11
Probability : Descriptive statistics
Lecture 3.12
Probability : Population vs samples
Lecture 3.13
Probability : Measures of Central Tendency & Variability
Lecture 3.14
Probability : Detection of Outliers
Lecture 3.15
Probability : Inferential Statistics
Lecture 3.16
Probability : Observational Studies and Experiments
Lecture 3.17
Probability : Sample and Population
Lecture 3.18
Probability : Population Distribution, Sample Distribution and Sampling Distribution
Lecture 3.19
Probability : Central Limit Theorem
Lecture 3.20
Probability : Point Estimates
Lecture 3.21
Probability : Confidence Intervals
Lecture 3.22
Probability : Introduction to Hypothesis Testing
Lecture 4.1
Introduction to Data Analytics with Python
Lecture 4.2
Python Basics
Lecture 4.3
Python Basics : Basic Syntax
Lecture 4.4
Python Basics : Data Types
Lecture 4.5
Python Basics : Operators
Lecture 4.6
Python Basics : Control flow statements
Lecture 4.7
Python Basics : Decisions
Lecture 4.8
Python Basics : Loops
Lecture 4.9
Python Basics : Functions
Lecture 4.10
Data Structures
Lecture 4.11
Data Structures : List and tuples
Lecture 4.12
Data Structures : Sets
Lecture 4.13
Data Structures : Dictionaries
Lecture 4.14
Data Structures: Strings
Lecture 4.15
Files and Databases
Lecture 4.16
Files and Databases : Reading from Files
Lecture 4.17
Files and Databases : Writing into files
Lecture 4.18
Files and Databases : Database connections
Lecture 4.19
Anaconda and Jupyter Notebook
Lecture 4.20
Anaconda and Jupyter :Notebook Introduction to Anaconda Distribution
Lecture 4.21
Introduction to the Jupyter Notebook : Introduction to the Jupyter Notebook
Lecture 4.22
Anaconda and Jupyter Notebook : Introduction to Regex Regular Expression
Lecture 4.23
Working with Matplotlib
Lecture 4.24
Working with NumPy
Lecture 4.25
Working with Pandas
Lecture 4.26
Visualization and plotting
Lecture 4.27
Web Scraping with Python
duration | 60 Hours |
---|---|
skill-level | Advanced |
language | English |
assessments | Classroom & Online |
after youu enlist in this course you'll recieve a call from our sales dpt. regarding our payment options
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