Course Contents
- Career building python course to make you succeed as a Data Scientist
- With Interactive Python Exercises you will get Hands on experience
- You will learn different data structures, functions, advance libraries like NUMPY, PANDAS, Matplotlib, SKLEARN, etc.
- You will e train on different Machine Learning Module
- Introduction to Data Science
- Data Science
- Data Scientists
- Examples of Data Science
- Data Science and Big Data
- Tools for Data Sciences Analysis
- Summary
- Data Analytics Overview
- Processes in Data Science
- Exploratory Data Analysis (EDA)
- Data Visualization
- Hypothesis Building
- Hypothesis Testing
- Summary
- Quiz
- Statistical Concepts & Business Applications
- Descriptive Statistics
- Statistical and Non-Statistical Analysis
- Measures of Central Tendency
- Knowledge Check
- Descriptive Statistics
- Bell Curve
- Symmetric Distribution
- Data Distribution
- Hypothesis Testing
- Chi-Square Test
- Correlation Matrix
- Applications of Inferential Statistics
- Summary
- Quiz
- Python: Environment Setup and Essentials
- Python Installation
- Python for Windows
- WinPython
- Anaconda
- Python Version
- Demo 1 - Python Installation using Anaconda distribution
- IPython Notebook
- The Jupyter Notebook
- Summary
- Quiz
- Summary of day's session
- Mathematical Computing with Python (Numpy)
- NumPy
- Attributes of ndarray Object
- Demo 1 - Create arrays in NumPy
- Demo 2 - Print arrays in NumPy
- Demo 3 - Basic operations in NumPy
- Knowledge Check 1
- Universal Functions (ufunc)
- Shape Manipulation
- Copy and Views
- Knowledge Check 2
- Broadcasting
- Knowledge Check 3
- Demo 4 - Indexing for arrays in NumPy
- Advanced Indexing
- Linear Algebra
- Mini Project 1
- Mini Project 2
- Summary
- Quiz
- Scientific computing with Python (Scipy)
- SciPy and its Characteristics
- Basics of NumPy
- SciPy Subpackage
- SciPy Subpackage—Integration
- Knowledge Check 2
- SciPy Subpackage—Optimize
- Linear Algebra
- Demo 1 - Calculate Eigenvalues
- Knowledge Check 1
- Demo 2 - Descriptive Statistics using SciPy
- Demo 3 - Solve svd
- Demo 4 -Calculate Norm
- SciPy Subpackages—Weave
- Demo 5 - Calculate File IO Value
- Mini Project 1
- Mini Project 2
- Summary
- Quiz
- Data Manipulation with Python (Pandas)
- Summary of day's session
- Introduction to Pandas
- Data Structures
- Series
- Knowledge Check 1
- DataFrame
- Data Viewing
- Demo 1 - How to view the data
- Knowledge Check 2
- Data Selection
- Demo 2 - Select data from data sets Part A
- Demo 3 - Select data from data sets Part B
- Panel
- Missing Data
- Knowledge Check 3
- Demo 4 - Manage missing data
- Operations on Data
- Mini Project 1
- Mini Project 2
- Summary
- Machine Learning with Python (Scikit-Learn)
- Quiz
- Machine Learning
- Supervised and Unsupervised Learning
- Scikit-Learn
- Knowledge Check 1
- Estimator Object
- Knowledge Check 2
- Regression Problem
- Demo 2 - Linear Regression
- Applications of Linear Regression
- Demo 3 - Logistic regression
- Clustering
- Demo 4 - Flat Clustering (K-means algorithm)
- Knowledge Check 3
- Dimensionality Reduction
- Demo 5 - Principal Component Analysis
- Demo 6 - Independent Component Analysis
- Demo 7 - Pipelining
- Demo 8 - Model Persistence
- Mini Project 1
- Mini Project 2
- Summary
- Quiz
- Summary of day's session
- Natural Language Processing with Python (Scikit-Learn)
- Natural Language Processing
- Knowledge Check 1
- NLP Libraries in Python
- Scikit-learn Operations
- Machine Learning on Text Data
- Mini Project 1
- Mini Project 2
- Summary
- Quiz
- Data Visualization in Python with Matplotlib
- Matplotlib
- Demo 1 - Plot with matplotlib- Not there.
- Line Properties
- Demo 2 - Create Different Subplots
- Layout
- Types of Plots
- Demo 3 - Create a histograms
- Demo 4 - Create pie chart
- Demo 5 - Create an errorbar plot
- Mini Project 1
- Mini Project 2
- Summary
- Web Scraping with Python
- Quiz
- Web Scraping
- BeautifulSoup
- Knowledge Check 1
- Extracting a Web Page
- Knowledge Check 2
- Parse Tree
- Demo 1 - Navigating the Tree
- Searching the Tree
- Knowledge Check 3
- Parsing a Part of the Document
- Demo 3 - Parsing Part of the document
- Mini Project 1
- Mini Project 2
- Summary
- Quiz
- Summary of day's session
N/A
Instructor Profile
Data Scientist with 10 years of experience executing data-driven solutions to increase efficiency, accuracy, and utility of internal data processing.
This course includes:
100% Online Sessions
Instructor led
Customizable Syllabus
Customizable Schedule
Certificate of Completion
Training Recordings
Training Resources
Learner Assessment
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