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The program objective is to academically prepare students in careers related to Data Science and Analytics. Include careers are Certified Database Administrators, Data Scientists, Database Developers, SQL Developers, and Analysts. Students will learn the role of enterprise data systems in business and why they are vital to the success of any organizations. Utilizing multiple medium to large scale datasets, students can expect to gain a large amount of knowledge in statistical analyses, data manipulation, and warehousing. Students will learn how to manage and maintain database systems across a broad range of enterprises, in addition to analyzing and designing applications that utilize and interface with Structure Query Language (SQL). This program covers the development of SQL databases, data mining and analysis with Python/R, data visualization, as well as writing and testing code by way of Microsoft SQL Server, PyCharm, and SQL Server Integration Services. At the end of this program, students will have the knowledge needed to pass the Microsoft Certified Solutions Associate or Expert exam.

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Associate Level (4 Months)

Occupations: Database Administrator, Database Developer, SQL Developer, Data Analyst, Business Intelligence Analyst, Business Analyst, Data Warehouse Analyst, Application Analyst, Software Analyst

Prerequisites: High School Diploma, or GED, or equivalent of a high school diploma from a home school.

Program Length: 450 hrs.

Cost: $7000 (Includes free laptop, course materials, and exam fees) – financial aid available.

Highlights: (Financial Aid offered, MCSA, Practicum, Job Placement)

This course is an overview of database administration and management practice including but not limited to performance, access, and security. This course will review the foundational concepts and cover the architecture, roles, and processes of being a database administrator. Topics will include the SQL programming language, managing schema projects, performing backups and recovery, administering alerts, and maintaining metrics.

  • Understanding Core Database Concepts
  • Creating Database Objects
  • Manipulating Data
  • Understanding Data Storage
  • Administering a Database

This course provides methodologies for extracting, transforming, loading, and querying large sums of data from relational databases. It serves as an introduction to many well-known database concepts, tasks, and techniques used for enterprise data mining. Using SQL Server Management Studio, students will learn the SQL programming language, SQL development, creating and dropping tables, querying, scalability, and data analysis.

  • Introduction to Microsoft SQL Server
  • Introduction to T-SQL
  • Writing SELECT
  • Querying Multiple
  • Sorting and Filtering Data
  • Working with SQL Server 2016 Data
  • Using DML to Modify
  • Using Built-In Functions
  • Grouping and Aggregating
  • Using Subqueries
  • Using Table Expressions
  • Using Set Operators
  • Using Windows Ranking, Offset, and Aggregate
  • Pivoting and Grouping Sets
  • Executing Stored Procedures

This course will teach you the skills for advanced database development. Students will learn about the production of cloud-based database systems and local database systems, along with building industry standard structures and designing healthy and efficient data warehousing systems.

  • Introduction to Database Development
  • Designing and Creating Tables
  • Advanced Table Designs
  • Designing and Implementing Views
  • Introduction to XML
  • User-Defined Functions

Students will learn industry standard warehouse design and manipulation utilizing large data sets within an enterprise system. Students will also gain a strong understanding for extracting, transforming, and loading large data sets from multiple remote and local sources.

  • Introduction to Data Warehousing
  • Designing and Implementing a Data Warehouse
  • Creating an ETL Solution
  • Implementing Control Flow in an SSIS Package
  • Debugging and Troubleshooting SSIS Packages

This course provides an introduction to the syntax, semantics, and structure of basic computer programming. Using the Python programming language, we will survey pragmatic applications for numerical computation, multivariate statistics, text processing, graphics, image processing, and networking, and their use in solving problems.

  • Python Basics
  • Numerical Computation
  • Multivariate Statistics
  • Text and Image Processing
  • Types and Sequences
  • Reading and Writing CSVs
  • This course introduces students to the various tools used for data cleansing and processing and Python. Students will learn how to read and create various dataframe structures and how to query and manipulate these structures. There will be a brief cover of statistical techniques used for dataframes such as distributions, sampling, and t-tests.
    • Pandas
    • Dataframes
    • Pandas Idioms
    • Connecting to a Database
    • SQL Execution with Python
    • Distributions and Hypothesis Testing

Leveraging Tableau, Excel, and other visual aspects of Python, you will be introduced to data visualization utilizing the various libraries and resources of these technologies as a means of demonstrating best practices for data visualization and generating key performance indicators. You will view examples from real world business cases and other related circumstances.

  • Principles of Data Visualization
  • Applied Plotting, Charting & Data Representation in Python
  • Introduction to Data Visualization with Excel
  • Pivot Tables
  • Pivot Charts
  • Downloading Data
  • Advanced SQL Integration in Excel

Survey course that allows students to choose an area of interest to apply the knowledge and skills gained throughout the program. Students will complete a project that must be approved by the instructor.

Students individually study to review and prepare for taking the Microsoft Solutions Certified Associate Certification. Upon completion students will also receive a Seikou Certification Completion Certificate.

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Expert Level (8 Months)

Occupations: Data Architect, Data Network Engineer, Data Application Manager, Database Administrator, Database Developer, SQL Developer, Data Analyst, Business Intelligence Analyst, Business Analyst, Data Warehouse Analyst, Application Analyst, Software Analyst

Prerequisites: MCSA Certification – Data Science Associate Level Completion

Program Length: 900 hrs.

Cost: $14000 (Includes free laptop, course materials, and exam fees)

Highlights: (Financial Aid offered, MCSA and MCSE Certification, Internship, Job Placement)

This course is an overview of database administration and management practice including but not limited to performance, access, and security. This course will review the foundational concepts and cover the architecture, roles, and processes of being a database administrator. Topics will include the SQL programming language, managing schema projects, performing backups and recovery, administering alerts, and maintaining metrics.

  • Understanding Core Database Concepts
  • Creating Database Objects
  • Manipulating Data
  • Understanding Data Storage
  • Administering a Database

This course provides methodologies for extracting, transforming, loading, and querying large sums of data from relational databases. It serves as an introduction to many well-known database concepts, tasks, and techniques used for enterprise data mining. Using SQL Server Management Studio, students will learn the SQL programming language, SQL development, creating and dropping tables, querying, scalability, and data analysis.

  • Introduction to Microsoft SQL Server
  • Introduction to T-SQL
  • Writing SELECT
  • Querying Multiple
  • Sorting and Filtering Data
  • Working with SQL Server 2016 Data
  • Using DML to Modify
  • Using Built-In Functions
  • Grouping and Aggregating
  • Using Subqueries
  • Using Table Expressions
  • Using Set Operators
  • Using Windows Ranking, Offset, and Aggregate
  • Pivoting and Grouping Sets
  • Executing Stored Procedures

This course will teach you the skills for advanced database development. Students will learn about the production of cloud-based database systems and local database systems, along with building industry standard structures and designing healthy and efficient data warehousing systems.

  • Introduction to Database Development
  • Designing and Creating Tables
  • Advanced Table Designs
  • Designing and Implementing Views
  • Introduction to XML
  • User-Defined Functions

Students will learn industry standard warehouse design and manipulation utilizing large data sets within an enterprise system. Students will also gain a strong understanding for extracting, transforming, and loading large data sets from multiple remote and local sources.

  • Introduction to Data Warehousing
  • Designing and Implementing a Data Warehouse
  • Creating an ETL Solution
  • Implementing Control Flow in an SSIS Package
  • Debugging and Troubleshooting SSIS Packages

Students individually study to review and prepare for taking the Microsoft Solutions Certified Associate Certification.

This course teaches the basics of programming computers using Python. We cover the basics of how one constructs a program from a series of simple instructions in Python. There are no prerequisites required.

  • Python Basics
  • Numerical Computation
  • Multivariate Statistics
  • Text and Image Processing
  • Types and Sequences
  • Reading and Writing CSVs

This course introduces students to the various tools used for data cleansing and processing and Python. Students will learn how to read and create various dataframe structures and how to query and manipulate these structures. There will be a brief cover of statistical techniques used for dataframes such as distributions, sampling, and t-tests.

  • Pandas
  • Dataframes
  • Pandas Idioms
  • Connecting to a Database
  • SQL Execution with Python
  • Distributions and Hypothesis Testing

Leveraging Tableau, Excel, and other visual aspects of Python, you will be introduced to data visualization utilizing the various libraries and resources of these technologies as a means of demonstrating best practices for data visualization and generating key performance indicators. You will view examples from real world business cases and other related circumstances.

  • Principles of Data Visualization
  • Applied Plotting, Charting & Data Representation in Python
  • Introduction to Data Visualization with Excel
  • Pivot Tables
  • Pivot Charts
  • Downloading Data
  • Advanced SQL Integration in Excel

In this course, you will learn practical ways of improving productivity and processes by utilizing automation with Python. The course will provide you with the tools necessary to help guide you through making real world business decisions without having to manually complete them yourself. Students will be able to automate reports, schedule tasks, automatically send text messages and other notifications pending performance issues, and data error handling.

  • Automate tasks by writing simple Python programs.
  • Text pattern recognition with Regular Expressions
  • Generating and Updating Reports with Python
  • Parse PDFs and Word documents.
  • Website Crawling
  • Autocommunication
  • Data Health – A module in Unit Testing

This course introduces students to the core concepts of teaching a computer to learn concepts using data without the need for being explicitly programmed. In the course students will receive a broad introduction to machine learning, datamining, and statistical pattern recognition. At the end of the course, students will be able to quickly apply industry standard learning techniques to new issues and problems.

  • What is Machine Learning?
    Supervised Learning
    Linear Regression
    Octave/Matlab
    Logistic Regression
    Regularization
    Neural Networks
    System Design
    Unsupervised Learning
    Recommender Systems

This course introduces students to the Hadoop framework, one of the largest big data frameworks in the industry. You will learn the specific components and basic processes utilized within the Hadoop architecture. The course will also introduce the basic concepts of the MapReduce model.

  • What is Big Data
  • MapReduce model
  • HDFS Basics
  • Hadoop Clusters
  • Hadoop Development Basics

Students individually study to review and prepare for taking the Microsoft Solutions Certified Expert Certification.

Survey course that allows students to choose an area of interest to apply the knowledge and skills gained throughout the program. Students may either take part in an internship or complete a project that must be approved by the instructor. The practicum cannot be completed until the student has passed 1 of the required certification exams for this program.

The objective of this course is to assist students in making career choices. This course focuses on self-assessment in terms of educational and career opportunities and reasonable possibilities in the world of work. It includes assessment for personal/career interests, values, needs, attitudes, skills, and other potential, and exploration of occupational information to establish career and educational goals. Upon completion of this course, students will be prepared to make sound career choices.

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