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- Data Analytics Course & Training Centre, Indore
Curriculum
- 13 Sections
- 107 Lessons
- 10 Weeks
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- Python fundamentals8
- Numpy10
- 2.1Introduction to Numpy and Why to learn Numpy10 Minutes0 Questions
- 2.2Intalling and Importing10 Minutes0 Questions
- 2.3Numpy array introduction10 Minutes0 Questions
- 2.4Ways of creating Numpy arrays10 Minutes0 Questions
- 2.5Slicing and Indexing10 Minutes0 Questions
- 2.6Reshaping array10 Minutes0 Questions
- 2.7Changing array dimension10 Minutes0 Questions
- 2.8Statistical and mathematical function10 Minutes0 Questions
- 2.9Random Number Generation10 Minutes0 Questions
- 2.10Handling Missing values10 Minutes0 Questions
- Pandas18
- 3.1Introduction to pandas and what it is used fo?
- 3.2Installation and importing
- 3.3Series vs Dataframe
- 3.4Creating Dataframe and series using List, dictionaries and numpy arrays
- 3.5Setting index
- 3.6Attributes head(), tail(), sample()
- 3.7Statistical description
- 3.8Loc and iLoc
- 3.9Renaming the column name
- 3.10Adding new column
- 3.11Dropping columns and rows
- 3.12conditional filtering using “&” and “|”
- 3.13apply function on single column
- 3.14apply func on multiple column using lambda func
- 3.15sorting method
- 3.16Value counts, unique, nunique, replace, map function
- 3.17Treatment of duplicate values
- 3.18Nlargest, Nsmallest
- Matplotlib (Data Visualization)10
- Seaborn (Data Visualization)13
- Plotly (Data Visualization)1
- Tableau (BI Tool)12
- Power Bi (BI Tools)10
- EDA10
- Statistics2
- SQL11
- Excel8
- Git and Github (optional)4