DATA SCIENCE WITH PYTHON PROGRAMMING
About the Course
In this course you will learn basics of the python programming
Duration: 40 hours
Mode: Classroom or Online Session
- Introduction
- Conditional Statement
- Lopping
- Control Statement
- String Manipulation
- List
- Tuple
- Dictionaries
- Functions
- Modules
- Input/Output
- Exception Handling
Content of Data Science
- Introduction
- Numphy
- Panda
- Mathplotlib
- Random Numbers
- Normal distribution
- Binomialrandom Numbers
Descriptive Statistics:
- Mean, Mode, Median
- Variance, Range
Pandas Library and Operations:
- Introduction to Pandas.
- Series
Group by
- Data Frames
- Merging, Joining, and
- Concatenating
- Missing Data
- Operations
- Pandas Exercises
Potting Using Pandas and Interpretation
- plot.barh
- pot.area
- plot.density
- plot.hist
- plot.line
- plot.scatter
- plot.bar
- plot.box
Descriptive Statistics (Theory, Examples and Code)
- Statistics Concepts
- Random variable
- Mean, Mode, Median,
- Quartiles, Percentile
Probability Distribution (Theory, Examples)
- Binomial distribution
- Poisson distribution
- Normal distribution
Correlation: (Theory, Examples and Code)
- Positive correlation
- Negative correlation
- Perfect and No correlation
Theory (Theory ,Example, Code)
- Intersection
- Union
- Difference
- Disjoint
- This course should be taken before any of the other Applied Data Science with Python courses: Applied Plotting, Charting & Data Representation in Python, Applied Machine Learning in Python, Applied Text Mining in Python, Applied Social Network Analysis in Python.
- Take tabular data, clean it, manipulate it, and run basic inferential statistical analyses.
- Understand techniques such as lambdas and manipulating csv files
- Describe common Python functionality and features used for data science
- Query DataFrame structures for cleaning and processing
- Explain distributions, sampling, and t-tests
Ganesh Kannan has more than 15 years of IT experience in Software testing, test Consulting, Project and Change management. He has worked for Investment Banks like Barclays Capital and IT services firm like Zensar Technologies. He has managed the testing tools and process function for a top tier investment bank and have managed large off-shore testing teams. He possess extensive project management and consulting experience in delivering IT applications and spearheads the classroom Fundamentals of software testing in Singapore.
