Dimension Tech

Data Analytics Course

More and more companies realize the importance of big data. Nowadays, no matter where you are in your career or what field you work in, you would better to know how to deal with data and interpret it. In other words, you should learn data analysis skill and apply tomorrow.

A data analyst collects, processes, and created visualization in order to gain insights form complex data sets. various data analysis method can be used to help us to interpret the data. We would lead you to get familiar with this track path from fundamental concept to advanced skill set. Moreover, essential topic like data manipulation, data visualization and statistics foundation are also included in our training course.
The Course outline is listed below. The cost of this course is: $13000.00

Chapter 1: Instruction of becoming a data analyst in an efficient way
Lesson 1: What is the general path for being a data analyst
Lesson 2: How to learn and practice in this course

Chapter 2: How to think like a data analyst 

Lesson 3: the reason of why we put this in beginning
Lesson 4: Structured principle of Data Analysis
Lesson 5: Formulation principle of Data Analysis
Lesson 6: Business principle of Data Analysis
Lesson 7:  Analysis with Quadrant Method
Lesson 8: Analysis with Multidimensional Method
Lesson 9: Analysis with hypothesis and Index Method
Lesson 10: Analysis with 28 Laws
Lesson 11: Analysis with Comparative Method
Lesson 12: Analysis with Funnel Method
Lesson 13: How those method used in real life work

Chapter 3: How analysis differ in business model
Lesson 14: why business is important to consider
Lesson 15: What Indicator matter in business analysis
Lesson 16: Using indicator to estimate Marketing
Lesson 17: Using indicator to estimate Product Operational
Lesson 18: Using indicator to estimate User Behavior
Lesson 19: Using indicator to estimate E-Commerce
Lesson 20: Using indicator to estimate Traffic
Lesson 21: crate a new indicator
Lesson 22: Build a Business Analysis Framework
Lesson 23: Introduction to Marketing Model
Lesson 24: classic AARRR Model
Lesson 25: Build a User Behavior Model
Lesson 26: Build a E-Commerce Model and a Traffic Model
Lesson 27: Business scenarios
Lesson 28: Practice for those scenarios
Lesson 29: Data Management In Business

Chapter 4: Handle Data With Spreed Sheet 
Lesson 30: Introduction to spreed sheet
Lesson 31: Text Cleaning
Lesson 32: Exercise for text Cleaning
Lesson 33: Matching command
Lesson 34: Logical statement in spreed sheet
Lesson 35:  Statistical pre-build methods in spreed sheet
Lesson 36: Time Series in spreed sheet
Lesson 37: Frequently Asked Questions
Lesson 38: Spreed Sheet Toolkit (1)
Lesson 39: Spreed Sheet Toolkit (2)
Lesson 40: Data Analysis with spreed sheet example (1)
Lesson 41: Data Analysis with spreed sheet example (2)

Chapter 5: Data Visualization 
Lesson 42:Why we care Data Visualization
Lesson 43: Fundamental Chart
Lesson 44: Advanced Chart Types
Lesson 45: Introduction to drawing tools
Lesson 46: visualization with spreed sheet based software
Lesson 47: Scatter graph
Lesson 48: strategy I — helper column

Lesson 49: bar graph
Lesson 50: Gantt diagram(1)
Lesson 51: Gantt diagram(2)
Lesson 52: FIG
Lesson 53: DuPont Analysis method
Lesson 54: Introduction to Power BI
Lesson 55: Power BI foundation
Lesson 56: Power BI advance strategy
Lesson 57: Practice with BI (1)
Lesson 58: Practice with BI (2)
Lesson 59: BI Dashboard

Chapter 6: SQL 
Lesson 60: Instruction to install SQL
Lesson 61: relational database
Lesson 62: Other type of database
Lesson 63: SQL select statement
Lesson 64: SQL conditional statement
Lesson 65: SQL group by statement
Lesson 66: SQL group by statement advanced strategy
Lesson 67: SQL builtin Function
Lesson 68: SQL Sub-query statement
Lesson 69: SQL join statement
Lesson 70: SQL Leetcode question set
Lesson 71: SQL Load data and Time
Lesson 72: practice SQL project(1)
Lesson 73: practice SQL project (2)
Lesson 74: using SQL with power bi

Chapter 7: Statistics foundation
Lesson 75: Descriptive Statistics concept
Lesson 76: Introduction to quantile
Lesson 77: Standard deviation
Lesson 78: Introduction to Weight
Lesson 79: Advance to weight
Lesson 80: Box Line diagram
Lesson 81: Histogram usage
Lesson 82: Introduction to Probability
Lesson 83: Introduction to Bayesian
Lesson 84: Introduction to Binomial Distribution
Lesson 85: Advance to Binomial Distribution
Lesson 86: Introduction to Poisson Distribution
Lesson 87: Introduction to Normal Distribution
Lesson 88:How to test your Hypothesis

Chapter 8: Data analysis with Python  
Lesson 89: Introduction to python
Lesson 90: Data Type in python
Lesson 91: Introduction to Variable
Lesson 92: Introduction to Listing
Lesson 93: Advanced to Listing
Lesson 94: Introduction to Dictionary
Lesson 95: Introduction to Collection
Lesson 96: Introduction to Control Flow
Lesson 97: How to use Control Flow Loop in python
Lesson 98: Python Loop advanced strategy
Lesson 99: Builtin Python Function
Lesson 100: advanced Function