Simplilearn Data Scientist Master's Program
4.6 /5- Offered bySimplilearn
- Private Institute
- Estd. 2010
Simplilearn Data Scientist Master's Program at Simplilearn Overview
Duration | 12 months |
Total fee | ₹49,990 |
Mode of learning | Online |
Difficulty level | Intermediate |
Credential | Certificate |
Simplilearn Data Scientist Master's Program at Simplilearn Highlights
- Job assistance with Simplilearn JobAssist
- Learn 30+ In-demand tools & skills along with 15+ Industry projects.
- *Easy EMI payment option available
- Exclusive hackathons and Live interactions with IBM leadership
- Access to IBM cloud platforms for 24x7 practice
Simplilearn Data Scientist Master's Program at Simplilearn Course details
- IT Professionals
- Analytics Managers
- Business Analysts
- Banking and Finance Professionals
- Marketing Managers
- Supply Chain Network Managers
- Recent Graduates in Bachelors/ Masters Degree
- Gain an in-depth understanding of data structure and data manipulation
- Understand and use linear and non-linear regression models and classification techniques for data analysis
- Obtain an in-depth understanding of supervised and unsupervised learning models such as linear regression, logistic regression, clustering, dimensionality reduction, K-NN, and pipeline
- Perform scientific and technical computing using the SciPy package and its sub-packages such as Integrate, Optimize, Statistics, IO, and Weave
- Gain expertise in mathematical computing using the NumPy and Scikit-Learn packages
- Understand the different components of the Hadoop ecosystem
- Learn to work with HBase, its architecture, and data storage, learning the difference between HBase and RDBMS, and use Hive and Impala for partitioning
- Understand MapReduce and its characteristics, plus learn how to ingest data using Sqoop and Flume
- Master the concepts of recommendation engine and time series modeling and gain practical mastery over principles, algorithms, and applications of machine learning
- Learn to analyze data using Tableau and become proficient in building interactive dashboards
- This Data Scientist Master's Program in collaboration with IBM accelerates your career in Data Science providing you with world-class training and skills required to become successful in this domain. The program offers extensive training on the most in-demand Data Science and Machine Learning skills with hands-on exposure to key tools and technologies including R, Python, Tableau, Hadoop, and Spark.
Simplilearn Data Scientist Master's Program at Simplilearn Curriculum
Introduction to Business Analytics
Overview
Business Decisions and Analytics
Types of Business Analytics
Applications of Business Analytics
Data Science Overview
Conclusion
Introduction to R Programming
Overview
Importance of R
Data Types and Variables in R
Operators in R
Conditional Statements in R
Loops in R
R script
Functions in R
Conclusion
Data Structures
Overview
Identifying Data Structures
Demo Identifying Data Structures
Assigning Values to Data Structures
Data Manipulation
Demo Assigning values and applying functions
Conclusion
Data Visualization
Overview
Introduction to Data Visualization
Data Visualization using Graphics in R
ggplot2
File Formats of Graphic Outputs
Conclusion
Statistics for Data Science-I
Overview
Introduction to Hypothesis
Types of Hypothesis
Data Sampling
Confidence and Significance Levels
Conclusion
Statistics for Data Science-II
Overview
Hypothesis Test
Parametric Test
Non-Parametric Test
Hypothesis Tests about Population Means
Hypothesis Tests about Population Variance
Hypothesis Tests about Population Proportions
Conclusion
Regression Analysis
Overview
Introduction to Regression Analysis
Types of Regression Analysis Models
Linear Regression
Demo Simple Linear Regression
Non-Linear Regression
Demo Regression Analysis with Multiple Variables
Cross Validation
Non-Linear to Linear Models
Principal Component Analysis
Factor Analysis
Conclusion
Classification
Overview
Classification and Its Types
Logistic Regression
Support Vector Machines
Demo Support Vector Machines
K-Nearest Neighbours
Naive Bayes Classifier
Demo Naive Bayes Classifier
Decision Tree Classification
Demo Decision Tree Classification
Random Forest Classification
Evaluating Classifier Models
Demo K-Fold Cross Validation
Conclusion
Clustering
Overview
Introduction to Clustering
Clustering Methods
Demo K-means Clustering
Demo Hierarchical Clustering
Conclusion
Association
Overview
Association Rule
Apriori Algorithm
Demo Apriori Algorithm
Conclusion
Simplilearn Data Scientist Master's Program at Simplilearn Faculty details
Simplilearn Data Scientist Master's Program at Simplilearn Entry Requirements
- Minimum 3 years of work experience.
- Proficiency in English is mandatory.
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