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Data Analysis with Python, Pandas and NumPy

Develop essential data science & ai skills with expert instruction and practical examples.

Online Course
Self-paced learning
Flexible Schedule
Learn at your pace
Expert Instructor
Industry professional
Certificate
Upon completion
What You'll Learn
Master the fundamentals of data science & ai
Apply best practices and industry standards
Build practical projects to demonstrate your skills
Understand advanced concepts and techniques

Skills you'll gain:

Professional SkillsBest PracticesIndustry StandardsPython
Prerequisites & Target Audience

Skill Level

IntermediateSome prior knowledge recommended

Requirements

Basic understanding of data science & ai
Enthusiasm to learn
Access to necessary software/tools
Commitment to practice

Who This Course Is For

Professionals working in data science & ai
Students and career changers
Freelancers and consultants
Anyone looking to improve their skills
Course Information

About This Course

Data Analysis with Python is for everyone who would like to create meaningful insight out of the data with the power of Numpy, Pandas, Matplotlib & Seaborn. The course has the right recipe to equip student with the right set of skill to ingest, clean, merge, manipulate, transform and finally visualize the data to create the meaning out of the data at hand. The goal of this course is many fold:- To provide theoretical and practical understanding of data analysis with Python package like NumPy and Pandas.

- To provide the knowledge of visualization tool ( matplotlib and seaborn ) so that one will be able to visualize and make correct decision based on the data. - And finally practice with real life data to feel confident of the topic and be able to ready to work on data analysis project or interview. The whole project is divided into following module:- NumPy introduction- Pandas introduction (Series and dataframe objects )- Data ingestion & Storage ( CSV, Excel, SQLite, JSON, HTML, Pickle and HDF5 storage etc.

)- Data Preparation ( Identify missing data, Handle missing data, handling duplicate data, Data transformation, Manipulating Row & Columns, Bucket Analysis, Outlier detection, Sampling, Creating dummy variable etc. )- Data Wrangling ( Data Aggregation, Merging, Joins - Inner, Outer, Left & Right join, Join, Concatenate, Pivot, Melt etc. )- Data Aggregation (Split, Apply & Combine, GroupBy clause, Binning data, Pivot table and Cross tabulations etc.

)- Visualization ( MatplotLib, Pandas Object visualization, Seaborn )- Project - Practice data analysis with real life datasets.

Provider
Udemy
Estimated Duration
10-20 hours
Language
English
Category
Technology & Programming

Topics Covered

Data Science & AIPython

Course Details

Format
Online, Self-Paced
Access
Lifetime
Certificate
Upon Completion
Support
Q&A Forum
Course Details
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This course includes:

Lifetime access to course content
Access on mobile and desktop
Certificate of completion
Downloadable resources

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