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Linear: Sequential Order
Course Overview
Data Science is the study of the generalizable extraction of knowledge from data. This course serves as an introduction to the data science principlesrequired to tackle data-rich problems in business and academia, including: Statistical Interference, Machine Learning, Machine Learning algorithms, Classification techniques, Decision Tree, Clustering, Recommender Engines, Text Mining & Time series.
Course Description
The Data Science course enables you to gain knowledge of the entire life cycle of Data Science, analyze and visualize different data sets, different Machine Learning Algorithms like K-Means Clustering, Decision Trees, Random Forest, and Naive Bayes.
Before You Start
Duration:
Welcome to the Course
Duration:
What Do You Enjoy About Being a Data Scientist?
Duration:
What Does a Data Scientist Do?
Duration:
What Kind of Person Succeeds as a Data Scientist?
Duration:
What Skills Does a Data Scientist Need?
Duration:
What Advice Would You Give an Aspiring Data Scientist?
Duration:
Assessment
3 Questions
Getting Started with Data
Duration:
Sorting and Filtering Data
Duration:
Derived Data
Duration:
Highlighting Data
Duration:
Getting Started with Excel Online
Assessment
2 Questions
Aggregating Data
Duration:
Grouping and Summarizing Data
Duration:
Visualizing Data
Duration:
Analyzing Data in Excel Online
Assessment
3 Questions
Measuring Central Tendency
Duration:
Measuring Variance
Duration:
Skewed Distributions
Duration:
Working with Samples
Duration:
Correlation
Duration:
Hypothesis Testing
Duration:
A Handy Handout
Assessment
23 Questions
What is Machine Learning?
Duration:
Regression
Duration:
Classification
Duration:
Clustering
Duration:
Some Useful Resources
Assessment
32 Questions
Final Assessment
20 Questions
The certificate issued for the Course will have
Only the e-certificate will be made available. No Hard copies. The certificates issued by NITTTR Chandigarh, MHRD - Government of India and Million Lights. can be e-verifiable at www.ulektzskills.com/verify.
45 hours Learning Content
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