Course Content
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Module1: Introduction Data Science
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Module 2: Visualization & Summization (EDA)
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Module 3: Data Validation Normality Predictive Analytics: Supervised Learning Algorithms
- Part-5: Data Validation Data Normality
- Part – 6 Data Cleaning outlier treatment
- Part-7: Test of Hypothesis
- This data science certification course contains basics of the python programming such as lambdas, reading and manipulating CSV files, data manipulation and cleaning techniques using the popular python pandas data science library, abstraction of the Series and DataFrame. By the end of the data science certification course, you will be able to take tabular data and manipulate the basic inferential statistical analyses. To become pro, enroll into data science course training institute in Hyderabad.
- Part -5
- Part -6
- Part -7
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Module 4: Supervised Learning Algorithms with Applications in Predictive Analytics Advanced Analytics
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Module 5: Advanced Data Analytics (Unsupervised Learning Algorithms)
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Module 6 : Machine Learning/Artificial Intelligence Machine Learning Algorithms/AI
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Module 7
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Module 8 Python Programming for data Science
Part -3 Basic Probability for Business Issues :
- Conditional probability (linked with decision Tress Algorithms)
- Bayes’ Theorem probability (linked with Naïve Bayes Algorithms)
- Discrete Distributions
- Binomial Distribution
- Poisson Distribution
- Continuous Distributions
- Normal Distribution and Properties
- Standardized Distributions
