• Post category:StudyBullet-12
  • Reading time:4 mins read


Data Analysis In-Depth (With Python)

What you will learn

Data Analysis In-depth, Covers Introduction, Statistics, Hypothesis, Python Language, Numpy, Pandas, Matplotlib, Seaborn and Complete EDA

Completing this course will also make you ready for most interview questions for Data Analysts Role

This is Pre-requisite for Machine Learning, Deep Learning, Reinforcement Learning, NLP, and other AI courses

Includes Optional Project and path to success

Description

Data Analysis In-Depth (With Python)

1. What will students learn in your course?

Data Analysis In-depth, Covers Introduction, Statistics, Hypothesis, Python Language, Numpy, Pandas, Matplotlib, Seaborn and Complete EDA

Completing this course will also make you ready for most interview questions for Data Analysts Role

This is Pre-requisite for Machine Learning, Deep Learning, Reinforcement Learning, NLP, and other AI courses

Includes Optional Project and path to success

2. What are the requirements or prerequisites for taking your course?

No Pre-requisite required. Curiosity to learn.

3. Who is this course for?


Get Instant Notification of New Courses on our Telegram channel.


People looking to advance their career in Data Science and Data Analytics

Already working in Data Science/ Data Analyst Roles and want to clear the concepts

Want to make base strong before moving to Machine Learning, Deep Learning, Reinforcement Learning, NLP, and other AI courses

Currently working as Business Analyst / Analyzing data in Excel, Tableau, Qlik, Power BI, etc. And want to do scalable and automated analysis in Python.

4. Is this course in depth and will make industry ready?

Absolutely yes, it will make you ready to creach Data Analyst roles interview as well as it is pre requisite for Machine Learning, Deep Learning, etc

5. I am new to IT/Data Science, Will i understand?

Absolutely yes, it is taught in most simplest way for every one to understand

English
language

Content

Data Analysis In-Depth (In Python)

Day 1 – Introduction to Data Science
Day 2 – Introduction to Data Analytics
Day 3 – Statistics for Data Analysis – Scalar, Vectors and Matrix
Day 4 – Statistics for Data Analysis – Probability
Day 5 – Statistics for Data Analysis – Probability
Day 6 – Statistics for Data Analysis – Probability
Day 7 – Statistics for Data Analysis – Probability
Day 8 – Statistics for Data Analysis – Statistical Hypothesis
Day 9A – Statistics for Data Analysis – Statistical Hypothesis
Day 9B – Python for Data Analysis
Day 10 – Python for Data Analysis
Day 11 – Python for Data Analysis
Day 12 – Python for Data Analysis
Day 13 – Numpy
Day 14 – Pandas
Day 15 – Pandas
Day 16 – Pandas
Day 17 – Pandas
Day 18 – Seaborn
Day 19 A – Seaborn
Day 19 B – EDA
Day 20 A – EDA Cont
Day 20 B – What Next