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Join the Best Institute for Data Science Course in Delhi (Uttam Nagar, Dwarka Mod, Janakpuri)

Data Science Using Python

ObjectiveThis course will teach the learner the advance part of the Python programming environment, including lambdas, reading and manipulating CSV files, and the NumPy module. The course will cover data manipulation and cleaning techniques using the popular Python pandas data science library, as well as the abstraction of Series and DataFrame as central data structures for data analysis, as well as tutorials on how to effectively use functions like groupby, merge, and pivot tables. Students will be able to take tabular data, clean it, alter it, and execute basic inferential statistical analyses by the end of this course.

This data science course will teach you how to clean, analyze, and visualize data using the Python programming language.

Course Duration1 And Half Month

EligibilityKnowledge Of Python Required

Syllabus

Syllabus

Module Unit Duration(Theory) in Hours Duration(Theory) in Hours Learning Objectives (Learner will learn after completion of unit)
1. Python Language
, Structures, Programming
Contructs
6 9 -Write Programming in the Python Language.
-Extensively use conditional
2. Data Science Concept 2 3 1. The concept of Data Science
and Analytics and various
steps to achieve analysis.
3. Numpy 8 12 1. Scientific computing and
data analysis by understanding large
mulitidimensional arrays and matrices
2. Run Efficient operations on arrays
3. Work on high-level mathemetical
functions to operate on these arrays
4. Pandas 14 21 1. Data analysis after importing
data from various sources.
2.understand the Series and DataFrame as the central data Structures for data analysis.
3.Learn various functions, grouping for data analysis.
5. Statistical Concepts and Functions 6 9 1. The Statistical tool of python having ability to manipulate some Statistical data and calculate results of various Statistical operations.
2.Understand functions like mean, median, mode and standard deviatin.
3.Understand the concept of Correlation and Regression.
6. Matplotlib 6 9 1. Learn the python library used to create graphs and plots with just a few commands.
2.Understand pyplot and its feature of line styles, font properties, formatting axes etc.
3.Understand all aspects of the programmatical control of all the figures
7. GUI-Tkinter 4 6 1. The standard python interface to the Tk GUI tookit for creating quick and intuitive GUI.
2.The various widgets for input and theie event handling.
3.Integrating the data analysis and graphs in Tkinter.
8. Machine Learning 2 3 1. Overview of Machine Learning and its concept
Module Unit Written Marks (Max.)
1. Python Language, Structure, Programming Contructs 14
Data Science Concepts 6
Numpy 20
Pandas 24
Statistical Concepts and Functions 10
Matplotlib 10
GUI-Tkinter 12
Machine Learning-The Next Step 4
Total 100

Syllabus

Module Unit Duration(Theory) in Hours Duration(Theory) in Hours Learning Objectives (Learner will learn after completion of unit)
1. Python Language
, Structures, Programming
Contructs
6 9 -Write Programming in the Python Language.
-Extensively use conditional
2. Data Science Concept 2 3 1. The concept of Data Science
and Analytics and various
steps to achieve analysis.
3. Numpy 8 12 1. Scientific computing and
data analysis by understanding large
mulitidimensional arrays and matrices
2. Run Efficient operations on arrays
3. Work on high-level mathemetical
functions to operate on these arrays
4. Pandas 14 21 1. Data analysis after importing
data from various sources.
2.understand the Series and DataFrame as the central data Structures for data analysis.
3.Learn various functions, grouping for data analysis.
5. Statistical Concepts and Functions 6 9 1. The Statistical tool of python having ability to manipulate some Statistical data and calculate results of various Statistical operations.
2.Understand functions like mean, median, mode and standard deviatin.
3.Understand the concept of Correlation and Regression.
6. Matplotlib 6 9 1. Learn the python library used to create graphs and plots with just a few commands.
2.Understand pyplot and its feature of line styles, font properties, formatting axes etc.
3.Understand all aspects of the programmatical control of all the figures
7. GUI-Tkinter 4 6 1. The standard python interface to the Tk GUI tookit for creating quick and intuitive GUI.
2.The various widgets for input and theie event handling.
3.Integrating the data analysis and graphs in Tkinter.
8. Machine Learning 2 3 1. Overview of Machine Learning and its concept

Marks Distribution

Module Unit Written Marks (Max.)
1. Python Language, Structure, Programming Contructs 14
Data Science Concepts 6
Numpy 20
Pandas 24
Statistical Concepts and Functions 10
Matplotlib 10
GUI-Tkinter 12
Machine Learning-The Next Step 4
Total 100

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Start On April 28, 2016
Duration 2M
Level Beginner
Instution Adafa academia
Branch Oxford street
Seat avaiable 29
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