Advanced Data Science Certification
- Offered byThe knowledge academy
Advanced Data Science Certification at The knowledge academy Overview
Duration | 4 days |
Start from | Start Now |
Total fee | ₹49,995 |
Mode of learning | Online |
Official Website | Go to Website  |
Credential | Certificate |
- Overview
- Highlights
- Course Details
- Curriculum
- Admission Process
Advanced Data Science Certification at The knowledge academy Highlights
- Earn a certificate after completion of course
- Engage in activities, and communicate with your trainer and peers
Advanced Data Science Certification at The knowledge academy Course details
Experienced Data Analysts
Data Scientists
Machine Learning Engineers
Statisticians
Business Analysts
AI Developers
Entrepreneurs
Researchers
To provide a comprehensive understanding of basic and advanced data science concepts
To equip delegates with practical skills in tools such as Pandas and Power BI
To cover critical topics like NumPy arrays, regression analysis, and machine learning mathematics
To empower business analysts, data engineers, software developers, and executives with data science proficiency
To enable delegates to unravel complex patterns and make informed decisions through data-driven insights
To ensure delegates emerge as adept data scientists capable of tackling real-world data challenges
In today's data-driven world, the demand for professionals with expertise in data science is soaring, and this Advanced Data Science Certification in India stands as a beacon for individuals seeking to navigate the intricate landscape of data science
This 4-day Advanced Data Science Certification Course in India is designed to empower delegates with practical knowledge and hands-on skills
It delves into essential concepts such as working with time series, three-dimensional plotting, data analytics lifecycle phases, and data manipulation using Power BI
Advanced Data Science Certification at The knowledge academy Curriculum
Module 1: Python for Data Analysis - NumPy
Introduction to NumPy
NumPy Arrays
Aggregations
Computation on Arrays: Broadcasting
Comparison, Boolean Logic and Masks
Fancy Indexing
Sorting Arrays
NumPy’s Structured Arrays
Module 2: Python for Data Analysis – Pandas
Installing Pandas
Pandas Objects
Data Indexing and Selection
Operating on Data in Pandas
Handling Missing Data
Hierarchical Indexing
Concat and Append
Merge and Join
Aggregations and Grouping
Pivot Tables
Vectorized String Operations
Working with Time Series
Eval() and Query()
Module 3: Python for Data Visualization – Matplotlib
Overview
Object-Oriented Interface
Two interfaces
Simple Line Plots and Scatter Plots
Visualizing Errors
Contour Plots
Histograms, Binnings and Density
Customizing Plot Legends
Customizing Color Bars
Multiple Subplots
Text Annotation
Three-Dimensional Plotting
Module 4: Python for Data Visualization – Seaborn
Installing Seaborn and Load Dataset
Plot the Distribution
Regression Analysis
Basic Aesthetic Themes and Styles
Distinguish between Scatter Plots, Hexbin Plots and KDE Plots
Use Boxplots and Violin Plots
Compare the Use Cases of Swarn Plots, Bar Plots Strip Plots, and Categorical Plots
Recall Some of the Use Cases and Features of Seaborn
Module 5: Machine Learning
Introduction
Importance
Types
How Machine Learning Works
Machine Learning Mathematics
Module 6: Natural Language Processing
Introduction to NLP
NLP and Writing Systems
Advantages
NLP Applications
Module 7: Deep Learning
Introduction
Importance
Working
Module 8: Big Data
Big Data Analytics
State of Practice in Analytics
Main Roles for New Big Data Ecosystem
Phases of Data Analytics Lifecycle
Module 9: Working with Data in R
Data Manipulation in R
Data Clean Up
Reading and Exporting Data
Importing Data
Charts and Graphs
Module 10: Regression in R
Regression Analysis
Linear Regression
Logistic Regression
Multiple Regression
Normal Distribution
Binomial Distribution
Module 11: Modelling Data
What are Relationships
Viewing Relationships
Creating Relationships
Cardinality
Cross Filter Direction
What is DAX
Syntax
Functions
Row Context
Calculated Columns
Calculated Tables
Measures
Module 12: Shaping and Combining Data using Power BI
Query Editor
Shaping Data and Applied Steps
Advanced Editor
Formatting Data
Transforming Data
Combining Data
Module 13: Interactive Data Visualizations
Page Layout and Formatting
Multiple Visualization
Creating Charts
Using Geographic Data
Histograms
Power BI Admin Portal
Service Settings
Desktop Settings
Dashboard and Report Settings
Advanced Data Science Certification at The knowledge academy Admission Process
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