Course Course Summary Section 1 Content Section 1 Content Left Section 1 Content Right Credit Type: Course ACE ID: SKIL-0207 Organization: SkillSoft Corporation Location: Classroom-based Length: Self-paced, 28 hours Dates Offered: 10/1/2019 - 5/31/2023 Credit Recommendation & Competencies Section 2 Content Section 2 Content Left Section 2 Content Right Level Credits (SH) Subject Upper-Division Baccalaureate 3 Data Science Description Section 3 Content Section 3 Content Left Section 3 Content Right Objective: The course objective is to help prepare the learner for a role as a data scientist, with a focus on visualization, APIs, machine learning and deep learning algorithms. Learning Outcomes: Describe the principle of the four Vs of big data analytics Implement data ingestion using various technologies including NiFi, Sqoop, and Wavefront Apply and implement essential data correction techniques, transformation rules, deductive correction techniques, and predictive modelling using critical data analytical approaches Create and use real time dashboards with Tableau Use the NumPy, Pandas, and SciPy libraries to perform various statistical summary operations on real datasets Use Matplotlib to visualize datasets Use R to create plots and charts of data Describe what a Recommendation Engine does, how it can be used, and the types and reasons they are used Evaluate a Recommendation Engine by using known data and metrics to calculate the accuracy of recommendations List sources of data anomaly and compare the differences between data verification and validation Demonstrate how to facilitate contextual data and collective anomaly detection using scikit-learn Use machine learning methods and visualization tools to manage anomalies and improvise data for better data insights and accuracy Perform t-tests using the SciPy library to test hypotheses Calculate the skewness and kurtosis of data using SciPy Compute regressions using scikit-learn Valuate data using descriptive and inferential methods Discuss how the four Vs should be balanced in order to implement a successful big data strategy Use Seaborn to perform various data visualization tasks Analyze continuous and categorical variables in a dataset using various plotting options in Seaborn including box and violin plots and FacetGrids Apply data research techniques, including JMP measurement Implement data exploration using R, Python, linear algebra, and plots General Topics: The Four Vs of Data Data Driven Organizations Raw Data Ingestion and Statistical Analysis Raw Data Management and Decision Making Insights Real Time Dashboards with Tableau Crafting a Story with Data Storytelling with Tableau and PowerBI Data Visualization Using Python and Seaborn Advanced Data Visualization Using Python and Seaborn Using Python to Compute and Visualize Statistics Advanced Dashboards Using Python R Data Visualization Advanced Data Visualization Using R Data Recommendation Engines Data Insights, Anomalies, and Verification - Handling Anomalies Data Insights, Anomalies, and Verification - Machine Learning and Visualization Tools Applied Inferential Statistics Data Research Techniques Data Research Exploration Techniques Data Research Statistical Approaches Machine and Deep Learning Algorithms and Introduction Machine and Deep Learning Algorithms Regression and Clustering Machine and Deep Learning Algorithms Data Preperation in Pandas ML Machine and Deep Learning Algorithms Imbalanced Datasets Using Pandas ML Creating Data APIs Using Node.js Instruction & Assessment Section 4 Content Section 4 Content Left Section 4 Content Right Instructional Strategies: Computer Based Training Laboratory Practical Exercises Methods of Assessment: Examinations Quizzes Minimum Passing Score: 70% Supplemental Materials Section 5 Content Section 5 Content Left Section 5 Content Right Section 6 Content Section 6 Content Left Section 6 Content Right Button Content Rail Content 1 Other offerings from SkillSoft Corporation Agile for Software Development (SKIL-0216) AI Apprentice to AI Architect (SKIL-0210) Application Developer to Blockchain Solutions Architect (SKIL-0209) Apprentice Java Developer to Senior Java Developer (SKIL-0229) Apprentice Programmer Journey - Novice and Apprentice Programmer (SKIL-0214) Apprentice Programmer Journey - Web Programmer and Web Apps Developer (SKIL-0213) AWS Certified Solutions Architect - Associate (SKIL-0252) AWS Certified Solutions Architect - Professional (SKIL-0253) Business Analyst to Data Analyst (SKIL-0227) C Programming Proficiency (SKIL-0262) View All Courses Page Content