Data science with python
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Statistics Fundamentals
- Graphically Displaying Single Variable Graphically Displayi...
- Measures of Location Measures of Location
- Measures of Spread Measures of Spread
- Displaying relationship Displaying relations...
- Bivariate Data Bivariate Data
- Scatterplot Scatterplot
- Measures of association of two or more variables Measures of associat...
- Covariance and Probability Covariance and Proba...
- Joint Probability and independent events Joint Probability an...
- Conditional probability Conditional probabil...
- Bayes’ Theorem Bayes’ Theorem
- Prior, Likelihood and Posterior Prior, Likelihood an...
- Discrete Random Variable Discrete Random Vari...
- Probability Distribution of Discrete Random Variable Probability Distribu...
- Binomial Distribution Binomial Distributio...
- Continuous Random Variables Continuous Random Va...
- Probability Distribution Function Probability Distribu...
- Uniform Distribution Uniform Distribution
- Normal Distribution Normal Distribution
- Point Estimation Point Estimation
- Interval Estimation Interval Estimation
- Hypothesis Testing Hypothesis Testing
- Testing a one-sided Hypothesis Testing a one-sided ...
- Testing a two-sided Hypothesis Testing a two-sided ...
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Python Fundamentals
- Installation Installation
- Python Syntax Python Syntax
- Python-Variables & Data Types Python-Variables �...
- Python-Numbers Python-Numbers
- Strings Strings
- Squences Squences
- List List
- Tuples Tuples
- Ranges Ranges
- Dictionary Dictionary
- Sets Sets
- Operators Operators
- If….else…Statements If….else…...
- For Loop For Loop
- While Loop While Loop
- Break Break
- Continue Continue
- Pass Pass
- Date & Time Date & Time
- Packages & Modules Packages & Modu...
- Functions Functions
- Reading a File Reading a File
- Writing into a File Writing into a File
- Class & Objects Class & Objects
- Python Expectations Python Expectations
- Regular Exp Regular Exp
- Mathematics Mathematics
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Pandas Data Frame
- Creating a Pandas DataFrame Creating a Pandas Da...
- Dealing with Rows and Columns in Pandas DataFrame Dealing with Rows an...
- Indexing and Selecting Data with Pandas Indexing and Selecti...
- Boolean Indexing in Pandas Boolean Indexing in ...
- Conversion Functions in Pandas DataFrame Conversion Functions...
- Iterating over rows and columns in Pandas DataFrame Iterating over rows ...
- Working with Missing Data in Pandas Working with Missing...
- Working With Text Data Working With Text Da...
- Working with Dates and Times Working with Dates a...
- Merging, Joining and Concatenating Merging, Joining and...
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Classification on Numpy Topics
- ndarray ndarray
- Array Creations Array Creations
- Data Type Object(dtype)in Nympy Data Type Object(dty...
- Indexing Indexing
- Basic Slicing & Advance Indexing Basic Slicing &...
- Iterating Over Array Iterating Over Array
- Binary Operations Binary Operations
- Mathematical Function Mathematical Functio...
- String Operations String Operations
- Linear Algebra Linear Algebra
- Sorting,Searcching & Counting Sorting,Searcching &...
- Set1(Introduction) Set1(Introduction)
- Set2(Advanced) Set2(Advanced)
- Multiplication of two Matrices in Single Line using Numpy in python Multiplication of tw...
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Object-Oriented Conecpts Collection
- Class, Object and Members Class, Object and Me...
- Data Hiding and Object Printing Data Hiding and Obje...
- Inheritance, examples of an object, subclass and super Inheritance, example...
- Polymorphism in Python Polymorphism in Pyth...
- Class and static variable in Python Class and static var...
- Class method and static method in Python Class method and sta...
- Changing class members Changing class membe...
- Constructors in Python Constructors in Pyth...
- Destructors in Python Destructors in Pytho...
- First-class function First-class function
- str() vs repr() str() vs repr()
- str() vs vpr() str() vs vpr()
- Class and instance attribute Class and instance a...
- Metaprogramming with metaclasses Metaprogramming with...
- Reflection Reflection
- Barrier objects Barrier objects
- Timer objects Timer objects
- Garbage collection Garbage collection
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Functions
- Functions in Python Functions in Python
- class method vs static method in Python class method vs stat...
- Write an empty function in Python Write an empty funct...
- pass statement pass statement
- Yield instead of Return Yield instead of Ret...
- Return Multiple Values Return Multiple Valu...
- Partial Functions in Python Partial Functions in...
- First Class functions in Python First Class function...
- Precision Handling Precision Handling
- *args and **kwargs *args and **kwargs
- Python closures Python closures
- Function Decorators Function Decorators
- Decorators in Python Decorators in Python
- Decorators with parameters in Python Decorators with para...
- Memoization using decorators in Python Memoization using de...
- Python bit functions on int (bit_length, to_bytes and from_bytes) Python bit functions...
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Data Analysis
- Data visualization using Bokeh Data visualization u...
- Exploratory Data Analysis in Python Exploratory Data Ana...
- Exploratory Data Analysis in Python Exploratory Data Ana...
- Data Analysis and Visualization with Python Data Analysis and Vi...
- Math operations for Data analysis Math operations for ...
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Machine Learning with Python
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Recommender System
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Regression Intro & Data
- Regression – Features and Labels Regression – Featu...
- Regression – Training and Testing Regression – Train...
- Regression – Forecasting and Predicting Regression – Forec...
- Regression – Theory and how it works Regression – Theor...
- Regression – How to program the Best Fit Slope Regression – How t...
- Regression – How to program the Best Fit Line Regression – How t...
- Regression – R Squared and Coefficient of Determination Theory Regression – R Squ...
- Model evaluation methods Model evaluation met...
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Machine Learning- Clustering
- Handling Non-Numerical Data for Machine Learning Handling Non-Numeric...
- K-Means with Titanic Dataset K-Means with Titanic...
- K-Means from Scratch in Python K-Means from Scratch...
- Finishing K-Means from Scratch in Python Finishing K-Means fr...
- Hierarchical Clustering with Mean Shift Introduction Hierarchical Cluster...
- Introduction to Naive Bayes Classifier Introduction to Naiv...
- Naive Bayes Classifier with Scikit Naive Bayes Classifi...
- Introduction into Text Classification using Naive Bayes Introduction into Te...
- Python Implementation of Text Classification Python Implementatio...
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1. What is the difference between Caddgild Technologies & other Centers?
Ans: – Caddgild Technologies is a ISO 9001:2015 Certified Training Centers, which follows the Pre Described Training Format which gives the clear understanding of the Training Subject
2. Is Caddgild Technologies is registered?
Ans; – Yes, Caddgild Technologies is Registered under Government of Karnataka
3. Do we get a Separate Lab for Practicing?
Ans: – Yes Caddgild provides the separate Lab for students practicing, all classrooms are LED Connected to make sure our students feel comfortable
4. Will the Student gets Certificate for the course we enroll here?
Ans: – Yes All Our Courses are Certified Courses, So all the students who completes the training from Caddgild technologies will be awarded with Course completion Certificate
5. Will the Student Get Flexibility in paying the Fees?
Ans: – Yes, We have Flexible payment options for Students to make payments & we also provide Interest free EMI Options
6. Will the student get any Placement Assisstance?
Ans: – Yes, Every Student who joins for the courses will have a 100% Placement Assisstance with us
