Certified Data Science with Python Professional by Vskills
Course Highlights
- Government Certification
- Certification valid for life
- Lifelong e-learning access
- Learning Hours: 30+ hrs
- Life Time Job Support
- Job Profile Tagging
Skills you will learn!
Curriculum
5 Topics
Data Science Introduction and Use Cases
Data Science Roles and Lifecycle
Data Science Stages and Technologies
Data Science Technologies and Analytics
ML-Data and CRISP-DM
8 Topics
Statistics and Experiments
Types of Data and Descriptive Statistics
Random Variables and Normal Distribution
Histograms and Normal Approximation
Central Limit Theorem
Probability Theory
Binomial Theory - Expected Value and Standard Error
Hypothesis Testing
28 Topics
Introduction to Python
Starting with Python with Jupyter Notebook
Python Variables and Conditions
Python Iterations 1
Python Iterations 2
Python Lists
Python Tuples
Python Dictionaries 1
Python Dictionaries 2
Python Sets 1
Python Sets 2
NumPy Arrays 1
NumPy Arrays 2
NumPy Arrays 3
Pandas Series 1
Pandas Series 2
Pandas Series 3
Pandas Series 4
Pandas DataFrame 1
Pandas DataFrame 2
Pandas DataFrame 3
Pandas DataFrame 4
Pandas DataFrame 5
Pandas DataFrame 6
Python User-Defined Functions
Python Lambda Functions
Python Lambda Functions and Date-Time Operations
Python String Operations
9 Topics
Introduction to EDA
EDA Tools and Processes
EDA Project - 1
EDA Project - 2
EDA Project - 3
EDA Project - 4
EDA Project - 5
EDA Project - 6
EDA Project - 7
12 Topics
Introduction to Machine Learning
Machine Learning Terminology
History of Machine Learning
Machine Learning Use Cases and Types
Role of Data in Machine Learning
Challenges in Machine Learning
Machine Learning Lifecycle and Pipelines
Regression Problems
Regression Models and Performance Metrics
Classification Problems and Performance Metrics
Optimizing Classification Metrics
Bias and Variance
13 Topics
Linear Regression Introduction
Linear Regression - Training and Cost Function
Linear Regression - Cost Functions and Gradient Descent
Linear Regression - Practical Approach
Linear Regression - Feature Scaling and Cost Functions
Linear Regression OLS Assumptions and Testing
Linear Regression Car Price Prediction
Linear Regression Data Preparation and Analysis 1
Linear Regression Data Preparation and Analysis 2
Linear Regression Data Preparation and Analysis 3
Linear Regression Model Building
Linear Regression Model Evaluation and Optimization
Linear Regression Model Optimization
8 Topics
Logistic Regression Introduction
Logistic Regression - Logit Model
Logistic Regression - Telecom Churn Case Study
Logistic Regression - Data Analysis and Feature Engineering
Logistic Regression - Build the Logistic Model
Logistic Regression - Model Evaluation - AUC-ROC
Logistic Regression - Model Optimization
Logistic Regression - Model Optimization 2
5 Topics
Unsupervised Learning - K-Means Clustering
K-Means Clustering Computation
K-Means Clustering Optimization
K-Means - Data Preparation and Modelling
K-Means - Model Optimization
4 Topics
Naive Bayes Probability Model - Introduction
Naive Bayes Probability Computation
Naive Bayes - Employee Attrition Case Study
Naive Bayes - Model Building and Optimization
6 Topics
Decision Tree - Model Concept
Decision Tree - Learning Steps
Decision Tree - Gini Index and Entropy Measures
Decision Tree - Hyperparameter Tuning
Decision Tree - Iris Dataset Case Study
Decision Tree - Model Optimization using Grid Search Cross Validation
4 Topics
Random Forest - Ensemble Techniques Bagging and Random Forest
Random Forest Steps Pruning and Optimization
Random Forest - Model Building and Hyperparameter Tuning using Grid Search CV
Random Forest - Optimization Continued
5 Topics
Support Vector Machine Concepts
Support Vector Machine Metrics and Polynomial SVM
Support Vector Machine Project 1
Support Vector Machine Predictions
Support Vector Machine - Classifying Polynomial Data
4 Topics
Principal Component Analysis - Concepts
Principal Component Analysis - Computations 1
Principal Component Analysis - Computations 2
Principal Component Analysis Practical
1 Topic
Principal Component Analysis - Concepts
Certified Data Science with Python Professional
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