Advanced Big Data Analysis & Science
irna
Mon, 11/13/2023 - 08:14
Duration
3 Days
Exam Details
- Exam Code: B90.05: Advanced Big Data Analysis & Science
- Duration: 60 minutes
- A passing grade on Exam B90.05 is a requirement for the following certification(s):
– Certified Big Data Scientist - Availability:
Pearson VUE Testing Centers Worldwide, Pearson VUE Online Proctoring, On-Site Proctoring
Price
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This course delves into a range of advanced data analysis practices and analysis techniques that are explored within the context of Big Data. The course content focuses on topics that enable participants to develop a thorough understanding of statistical, modeling, and analysis techniques for data patterns, clusters and text analytics, as well as the identification of outliers and errors that affect the significance and accuracy of predictions made on Big Data datasets.
Key Outcomes
After this course you will know:
- Exploratory Data Analysis
- Classification
- Modeling
- Model Evaluation Measures
- Pattern Identification
- Outlier Detection
Objectives
- Modeling, Model Evaluation, Model Fitting and Model Overfitting
- Statistical Models, Model Evaluation Measures
- Cross-Validation, Bias-Variance, Confusion Matrix and F-Score
- Machine Learning Algorithms and Pattern Identification
- Association Rules and Apriori Algorithm
- Data Reduction, Dimensionality Feature Selection
- Feature Extraction, Data Discretization (Binning and Clustering)
- Advanced Statistical Techniques
- Parametric vs. Non-Parametric, Clustering vs. Non-Clustering
- Distance-Based, Supervised vs. Semi-Supervised
- Linear Regression and Logistic Regression for Big Data
- Classification Rules for Big Data
- Logistics Regression, Naïve Bayes, Laplace Smoothing, etc.
- Decision Trees for Big Data
- Tree Pruning, Feature Splitting, One Rule (1R) Algorithm
- Pattern Identification, Association Rules, Apriori Algorithm
- Time Series Analysis, Trend, Seasonality
- K Nearest Neighbor (kNN), K-means
- Text Analytics for Big Data
- Bag of Words, Term Frequency, Inverse Document Frequency, Cosine Distance, etc.
- Outlier Detection for Big Data
- Statistical, Distance-Based, Supervised and Semi-Supervised Techniques
Contact
- Nurman (+62 857-2375-3840)
- Irna (+62 822-1664-7749)
- Puji (+62 813-2424-2115)