About
This course teaches students everything required to be knowledgeable in the field of Data Science. Enrolling in this course would fill up your resume with in-demand skills like Statistical analysis, Python programming, NumPy, Pandas, Advanced Statistical Analysis, Power BI etc.
Perfect for students seeking a job in a versatile field with many options!
Learn from the Best
Data Science Megha Kansal
Course curriculum
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Promo Video
FREE PREVIEW -
Python Introduction P1
FREE PREVIEW -
Python Installation P2
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Python Installation P3
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Python Libraries And NB Intro
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Python Libraries And NB Intro part -2
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Jupyter Notebook
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Python Basics
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Python Basics part - 2
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Python Basics part - 3
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Data Type String
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Data Type Boolean And Built-In Functions
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Lists part - 1
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Lists part - 2
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Lists part - 3
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Lists part - 4
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List Exercise
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Dictionary
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Dictionary part - 2
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Tuples P1
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Tuples P2
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Sets P1
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Sets P2
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Sets P3
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Course Instruction
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Numpy
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Numpy Number Generating Techniques
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Numpy Indexing
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4- Numpy Indexing Part 2
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Pandas Basics
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Pandas Analyze Data
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Pandas Data Cleaning Part 1
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Pandas Null Duplicate Values (1)
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4 - Pandas Null Duplicate Values (2)
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Pandas Indexing
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Pandas Merge
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Quiz - 1
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Matplotlib (1)
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Matplotlib (2)
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Matplot figure function
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3 - Matplotlib bar
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Matplotlib Histo
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Statistics Basics Part 1
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Statistics Basics Part 2
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Statistics Basic 2 Data Collection Part 1
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Statistics Basic 2 Data Collection Part 2
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Desriptive Statistics
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4-Arithmatic Mean
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Median, Mode
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Measure of Spread- Range
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Measure of Spread-IQR-Part1
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Measure of Dispersion-IQR part 2
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Measure of Spread-IQR part 3
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Standard Deviation & Variance
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Standard Deviation & Variance Example
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Empirical Rule
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Z Score (1)
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Shape-Skweness
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Covariance
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Covariance Example
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Coefficient of Correlation
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Statistics in Python
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What is probability
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Types of Probability
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Mutually Exclusive Independent Event
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Union Intersection
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Exhaustive and Compliment
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Probabilty -Additional Rule
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Probability Additional Rule Example
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Probability Multiplication Rule
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Bayes Theorem
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Bayes Theorem Case Study
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Central Limit System
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Hypothesis Testing
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Hypothesis Type I & II Error
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Hypothesis Observed Value
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Hypothesis Level of Significance
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Hypothesis LOS Critical Value
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Hypothesis Testing Case Study
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P - value
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Degrees of Freedom
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T Test
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Chi Square test
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Chi-square test example in excel-part 1
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Chi square test example in excel-part 2
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QUIZ - 2
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Course Instruction
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Machine Learning Intro
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What is Machine Learning & Examples
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What is Supervised Learning
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4-Supervised Learning Example
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What is Unsupervised Learning
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Unsupervised Learning Example
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Linear Regression part1
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Linear Regression Rsquare
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Uses & Assumptions of Linear Regression
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Multiple Linear Regression
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Linear Regression-Python Model Creation & Prediction
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Model Evaluation
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Difference in Actual & Prediction
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Adjusted R-squared
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Collinearity
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What is Logistic Regression
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Logistics Regression Example
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18-Logistic Regression Equation
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Logistic Regression-Logit
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Confusion Matrix
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Logistic Regression ROC
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Logistic Regression AUC
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Logistic Regression Practical Python-part 1
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Logistic Regression -Python practical - Part 2
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Logistic Regression-Summary- part 3
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Logistic Regression-Python Practice-Predictions-part4
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Bias & Variance Trade off
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Overfitting & Underfitting
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What is K Nearest Neighbor (KNN)
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KNN Explanation
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KNN - How to compute
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KNN Python-Data Preprocession - part 1
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KNN Python-Model Creation-part2 (1)
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KNN Python-Model Creation-part2
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KNN Python-Prediction-part3
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Decision Tree
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Decision Tree Explanation
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Decision Tree-Python Case Study
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Decision Tree - Python Case Study - part 2
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Ensemble Technique - Bagging
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Boosting
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Random Forest
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Random Forest-Python Case Study
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What is Clustering
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Clustering Application & Flow
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Cluster-Distance
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Hierarchical Clustering
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Clustering Steps
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K-Means Clustering
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K Means Clustering Algorithm Python
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Machine Learning Complete Recape
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Quiz - 3
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About this course
- 159 lessons
- 17.5 hours of video content
What You'll Learn
Python:
Python Installation
Introduction to Python
Python Libraries And NB Intro
Jupyter Notebook
Python Basics
Data Type String
Data Type Booloean And Built-In Functions
Lists
List Exercise
Dictionary
Tuples
Sets
Numpy:
Numpy number Generating Techniques
Numpy Indexing
Functions and Arithmatic Operations
Pandas:
Pandas Basics
Pandas Analyse Data
Pandas Data Cleaning
Pandas Null Duplicate Values
Pandas Indexing
Pandas Merge
Data Visualization:
Matplotlib
Maplot figutre function
Matplotlib bar
Matplotlib Histo
Statistics:
Statistics Basics
Statistics Basic Data Collection
Desriptive Statistics
Arithmatic Mean
Median, Mode
Measure of Spread- Range
Measure of Spread-IQR-Part1
Measure of Dispersion-IQR part 2
Measure of Spread-IQR part 3
Standard Deviation & Variance
Standard Deviation & Variance Example
Empirical Rule
Z Score
Shape-Skweness
Covariance
Coefficient of Correlation
Statistics in Python
What is probability
Types of Probability
Mutually Exclusive Independent Event
Union Intersection
Exhaustive and Compliment
Probabilty -Additional Rule
Probability Multiplication Rule
Bayes Theorem
Central Limit System
Hypothesis Testing
Hypothesis Type I & II Error
Hypothesis Observed Value
Hypothesis Level of Significance
Hypothesis LOS Critical Value
Hypothesis Testing Case Study
p – value
Degrees of Freedom
t Test
Chi Square test
Chi-square test example in excel
Chi-square using python
Machine Learning:
Machine Learning Intro
What is Machine Learning & Examples
What is Supervised Learning and Examples
What is Unsupervised Learning and Examples
Linear Regression
Linear Regression Rsquare
Uses & Assumptions of Linear Regression
Multiple Linear Regression
Linear Regression-Python Model Creation & Prediction
Model Evaluation
Difference in Actual & Prediction
Adjusted R-squared
Collinearity
What is Logistic Regression
Logistics Regression Example
Logistic Regression Equation
Logistic Regression-Logit
Confusion Matrix
Logistic Regression ROC
Logistic Regression AUC
Logistic Regression Practical Python
Logistic Regression -Python practicle
Logistic Regression-Python Practice-Predictions
Bias & Variance Tradeoff
Overfitting & Underfitting
What is K Nearest Neighbor (KNN)
KNN Explanation
KNN - How to compute
KNN Python-Data Preprocession
KNN Python-Model Creation
KNN Python-Prediction
Decision Tree
Decision Tree-Python Case Study
Ensemble Technique – Bagging
Boosting
Random Forest
Random Forest-Python Case Study
What is Clustering
Clustering Application & Flow
Cluster-Distance
Hierarchical Clustering
Clustering Steps
K-Means Clustering
K Means Clustering Algorithm Python
Power BI:
Power BI Intro
Power BI Installation & About Power BI
Power BI-Tour
Get Data
Edit Query
Power BI Transform Data
Data Modelling
Visualization
What this Course Includes
- 151 videos
- 17 hours of on-demand video
- 4 Quizzes and 1 final Exam
- 1 Real-Life Projects
- Access on mobile, Laptop, and TV
- Lifetime access to videos anytime, anywhere
- Certificate of completion by Skillarena
- Guaranteed Internship
Requirements
System Pre-requisites:-
- 8GB RAM Recommended
- Windows 10 is recommended.
- Browsers - Edge, Chrome.
- At least 500 GB of Hard Disk would be the minimum requirement as data sets you practice tend to be heavy.
- Willingness to Learn and Explore