About this Course
Learn to analyze information utilizing Python. This course will take you from the fundamentals of Python to exploring many several types of information. You’ll discover ways to put together information for evaluation, carry out easy statistical evaluation, create significant information visualizations, predict future traits from information, and extra!
- IBM Information Science Skilled Certificates
- IBM Information Analyst Skilled Certificates
WHAT YOU WILL LEARN
Describe Python information acquisition and evaluation methods.
Analyze Python information utilizing a dataset.
Determine three Python libraries and describe their makes use of.
Learn information utilizing Python’s Pandas package deal.
SKILLS YOU WILL GAIN
- Predictive Modelling
- Python Programming
- Information Evaluation
- Information Visualization (DataViz)
- Mannequin Choice
Syllabus – What you’ll study from this course
2 hours to finish
Importing Datasets
On this module, you’ll discover ways to perceive information and study tips on how to use the libraries in Python that will help you import information from a number of sources. You’ll then discover ways to carry out some fundamental duties to start out exploring and analyzing the imported information set.
2 hours to finish
Information Wrangling
On this module, you’ll discover ways to carry out some basic information wrangling duties that, collectively, type the pre-processing part of information evaluation. These duties embrace dealing with lacking values in information, formatting information to standardize it and make it constant, normalizing information, grouping information values into bins, and changing categorical variables into numerical quantitative variables.
2 hours to finish
Exploratory Information Evaluation
On this module, you’ll study what is supposed by exploratory information evaluation, and you’ll discover ways to carry out computations on the info to calculate fundamental descriptive statistical info, resembling imply, median, mode, and quartile values, and use that info to higher perceive the distribution of the info. You’ll study placing your information into teams that will help you visualize the info higher, you’ll discover ways to use the Pearson correlation technique to check two steady numerical variables, and you’ll discover ways to use the Chi-square check to search out the affiliation between two categorical variables and tips on how to interpret them.
2 hours to finish
Mannequin Improvement
On this module, you’ll discover ways to outline the explanatory variable and the response variable and perceive the variations between the easy linear regression and a number of linear regression fashions. You’ll discover ways to consider a mannequin utilizing visualization and study polynomial regression and pipelines. Additionally, you will discover ways to interpret and use the R-squared and the imply sq. error measures to carry out in-sample evaluations to numerically consider our mannequin. And lastly, you’ll study prediction and choice making when figuring out if our mannequin is appropriate.
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