- enquiry@crystaltrainingsolutions.com
- Call us +91 9108050078
Unit – 1: Advanced Excel Course – Overview of the Basics of Excel
• Customizing common options in Excel
• Absolute and relative cells
• Protecting and un-protecting worksheets and cells
Unit – 2: Advanced Excel Course – Working with Functions
• Writing conditional expressions (using IF)
• Using logical functions (AND, OR, NOT)
• Using lookup and reference functions (VLOOKUP, HLOOKUP, MATCH, INDEX)
• VlookUP with Exact Match, Approximate Match
• Nested VlookUP with Exact Match
• VlookUP with Tables, Dynamic Ranges
• Nested VlookUP with Exact Match
• Using VLookUP to consolidate Data from Multiple Sheets
Unit – 3: Advanced Excel Course – Data Validations
• Specifying a valid range of values for a cell
• Specifying a list of valid values for a cell
• Specifying custom validations based on formula for a cell
Unit – 4: Advanced Excel Course – Working with Templates
• Designing the structure of a template
• Using templates for standardization of worksheets
Unit – 5: Advanced Excel Course – Sorting and Filtering Data
• Sorting tables
• Using multiple-level sorting
• Using custom sorting
• Filtering data for selected view (AutoFilter)
• Using advanced filter options
Unit –6: Advanced Excel Course – Working with Reports
• Creating subtotals
• Multiple-level subtotals
• Creating Pivot tables
• Formatting and customizing Pivot tables
• Using advanced options of Pivot tables
• Pivot charts
• Consolidating data from multiple sheets and files using Pivot tables
• Using external data sources
• Using data consolidation feature to consolidate data
• Show Value as (% of Row, % of Column, Running Total, Compare with Specific Field)
• Viewing Subtotal under Pivot
• Creating Slicers
Unit – 7: Advanced Excel Course – More Functions
• Date and time functions
• Text functions
• Database functions
• Power Functions (CountIf, CountIFS, SumIF, SumIfS)
Unit – 8: Advanced Excel Course – Formatting
• Using auto formatting option for worksheets
• Using conditional formatting option for rows, columns and cells
Unit – 9: Advanced Excel Course – Macros
• Relative & Absolute Macros
• Editing Macro’s
Unit – 10: Advanced Excel Course – WhatIf Analysis
• Goal Seek
• Data Tables
• Scenario Manager
Unit – 11: Advanced Excel Course – Charts
• Using Charts
• Formatting Charts
• Using 3D Graphs
• Using Bar and Line Chart together
• Using Secondary Axis in Graphs
• Sharing Charts with PowerPoint / MS Word, Dynamically
• (Data Modified in Excel, Chart would automatically get updated)
• Introduction of Power BI
• What is Power BI
• Why you should learn Power BI
• Power BI Architecture
• Power BI Components
• Download and Install BI Desktop
• Add, Rename, Duplicate, and Delete Pages
• Connect to SQL Server
• Connect to Multiple Excel Sheets
• Get Data from Excel Files
• Get Data from Text Files
• Load Data from Multiple Data Sources
• Remove Unwanted Columns from Tables
POWER BI TRANSFORMATIONS
• Change the Data type of a Column
• Combine Multiple Tables
• Clusters
• Enter data or Copy & Paste data from Clipboard
• Format Dates
• Groups
• Hierarchies
• Joins
• Pivot Table
• Query Groups
• Reorder or Remove Columns
• Rename Column Names
• Rename Table Names
• Split Columns
• UnPivot Table
POWER BI CHARTS TUTORIAL
• Area Chart
• Bar Chart
• Card
• Clustered Bar Chart
• Clustered Column Chart
• Column Chart
• Donut Chart
• Funnel Chart
• Heat Map
• Line Chart
• Clustered Column and Line Chart
• Line and Stacked Column Chart
• Matrix
• Multi-Row Card
• Pie Chart
• Ribbon Chart
• Stacked Area Chart
• Scatter Chart
• Stacked Bar Chart
• Stacked Column Chart
• Table
• Tree Map
• Waterfall Chart
• 100% Stacked Bar Chart
• 100% Stacked Column Chart
• Map
• Filled Map
• Format Area Chart
• Format Bar Chart
• Formatting Card
• Format Clustered Bar Chart
• Format Clustered Column Chart
• Formatting Column Chart
• Format Donut Chart
• Format Funnel Chart
• Formatting Line Chart
• Format Line & Clustered Column
• Format Line & Stacked Column
• Formatting Matrix
• Format Multi-Row Card
• Format Pie Chart
• Formatting Ribbon Chart
• Format Stacked Area Chart
• Formatting Scatter Chart
• Format Stacked Bar Chart
• Formatting Stacked Column Chart
• Format Table
• Format Tree Map
• Formatting Waterfall Chart
• R Script
• Format Map
• Format Filled Map
POWER BI FILTERS TUTORIAL
• Slicer
• Basic Filters
• Advanced Filters
• Top N Filters
• Filters on Measures
• Page Level Filters
• Report Level Filters
• Drill through Filters
POWER BI TUTORIAL ON CALCULATED FIELDS
• Calculated Columns
• Conditional Columns
• Calculated Measures
• Calculated Tables
• Custom Columns
POWER BI TUTORIAL ON DASHBOARDS
• Register to Pro Service
• Dashboard Introduction
• Connect Desktop with BI Service or Pro
• Publish Desktop Reports
• Create a Workspace
• Create a Dashboard
• Favorites
WORKING WITH POWER BI DASHBOARDS
• Dashboard Actions
• Add Reports to a Dashboard
• Add Title to Dashboard
• How to Add Image to Dashboard
• Add Video to Dashboard
• Add Web Content to Dashboard
• Dashboard Settings
• Delete a Dashboard
• Pin Report to a Dashboard
SHARING POWER BI WORK
This Power Bi tutorial section covers the sharing of Work. I means, sharing reports, Dashboards, apps, Workspaces etc.
• Share a Dashboard
• Share a Report
• Sharing Workspace
• Publish App
• View Published App
POWER BI DAX
• Aggregate Functions
• Date Functions
• Logical Functions
• Math Functions
• String Functions
• Trigonometric Functions
Introduction to SQL
• Retrieving Data
• Updating Data
• Inserting Data
• Deleting Data
• Sorting and Filtering Data
• Advanced Filtering
• Summarizing Data
• Grouping Data
• Using Sub queries
• Joining Tables
• Managing Tables
• Using Views
• Stored Procedures
• Using Cursors
• Using Transactions
Course Introduction and Overview
Unit – 1: Sheet related Activities
• Simple data
• If statements
• Tool box controls
• Loops
• Multiple loops
• Data filtering & populating to listbox
• Data filtering & populating to another column in the same sheet
• Font related activities
• Font color activities
• Cells formatting activities
• Cells fill color activities
• Sheets renaming, protecting
• Sheets sorting
• Data sorting
• Blank rows, columns deleting
• Hide, unhide rows, cols
• Workbook save, delete activities
• Range, cells controlling
Unit – 2: Multiple sheets data activities
Unit – 3: Chart related activities
Unit – 4: Msgbox related activities
Unit – 5: Other applications related activities
Unit – 6: Transferring data from excel to word, access, and pdf files
Unit – 7: Administrator related activities
Unit – 8: Pivot Tables and Pivot Chart Related Programs
Note: Each topics contains multiple programs and scenarios
Unit 1 – Introduction to Python
Unit 2 – Basic Python
Unit 3 – Working with Libraries Like NumPy, Pandas, Matplotlib, Seaborn, SciPy, Sklearn in Python
Unit 4 – Working Experience with Pandas In Python
Unit 5 – Working Experience with Matplotlib Library in Python
Unit 6 – To Work With Seaborn Library (High-Level Interface for Drawing Attractive and Informative Statistical Graphics) In Python
Unit 7 – Introduction to SciPy and Sklearn Libraries in Python
Unit 8 – Statistical Analysis
Unit 9 – Hypothesis Testing
Unit 10 – Linear Regression
Unit 11 – Logistic Regression
Unit 12 – Discrete Probability Distribution
Unit 13 – Advanced Regression
Unit 14 – Multinomial Regression
Unit 15 – Data Mining Unsupervised – Clustering
Unit 16 – Dimension Reduction
Unit 17 – Data Mining Unsupervised – Network Analytics
Unit 18 – Data Mining Unsupervised – Association Rules
Unit 19 – Data Mining Unsupervised – Recommender System
Unit 20 – Machine Learning Classifiers – KNN
Unit 21 – An Introduction to Data Visualization
Unit 22 – Tableau Products and Usage
Unit 23 – Basic Charts On Tableau
Unit 24 – Connecting Tableau with Multiple Sheets and Data Sources
Unit 25 – Tableau Filters and Visualization Interactivity
Unit 26 – Interaction and Grouping the Data
Unit 27 – Time Series Chart
Unit 28 – Maps and Images in Tableau
Unit 29 – Advanced Charts in Tableau and Analytical Techniques
Unit 30 – Calculations on Tableau
Unit 31 – Tableau Integration with Other Tools
Unit 32 – Understand the Business Problem
Unit 33 – Data Collection
Unit 34 – Data Cleansing / Exploratory Data Analysis / Feature Engineering
Unit 35 – Data Mining
Unit 36 – Model Deployment
Unit 37 – Introduction to Big Data
Unit 38 – Hadoop and Its Components
Unit 39 – Linux OS and Virtualization Software’s
Unit 40 – Apache Hive
Unit 41 – Apache SQOOP
Unit 42 – Apache Spark
Unit 43 – Classifier – Naive Bayes
Unit 44 – Bagging and Boosting
Unit 45 – Decision Tree and Random Forest
Unit 46 – Black Box Methods
Unit 47 – Text Mining
Unit 48 – Natural Language Processing
Unit 49 – Forecasting
Unit 2 – Linear Regression and Feature Selection
Unit 3 – Linear Classification
Unit 4 – Support Vector Machines and Artificial Neural Networks
Unit 5 – Bayesian Learning and Decision Trees
Unit 6 – Evaluation Measures
Unit 7 – Hypothesis Testing
Unit 8 – Ensemble Methods
Unit 9 – Clustering
Unit 10 – Graphical Models
Unit 11 – Learning Theory and Expectation Maximization
Python Training Overview
• What are the Python Course Pre-requisites
• Objectives of the Course
• Who should do the course
• Python Training Course Duration
Python Course Content
• Introduction to Script
• Introduction to Python
• Different Modes in PYTHON
• PYTHON NEW IDEs
• Variables in Python
• String Handling
• Python Operators and Operands
• Python Conditional Statements
• Python LOOPS
• Learning Python Strings
• Sequence or Collections in PYTHON
• Python Lists
• Python TUPLE
• Python Sets
• Python Dictionary
• Python Functions
Advanced Python
• Python Modules
• Packages in Python
• Python Date and Time
• File Handling
• Python OS Module
• Python Exception Handling
• More Advanced PYTHON
• Python Class and Objects
• Python Regular Expressions
• Python XML Parser
• Python-Data Base Communication
• Multi-Threading
• Web Scrapping
• Unit Testing with PyUnit
• Introduction to Python Web Frameworks
• GUI Programming-Tkinter
Unit 1: Introduction and Overview
• Why Tableau? Why Visualization?
• Level Setting – Terminology
• Getting Started – creating some powerful visualizations quickly
• The Tableau Product Line
• Things you should know about Tableau
Unit 2: Getting Started
• Connecting to Data and introduction to data source concept
• Working with data files versus database server
• Understanding the Tableau workspace
• Dimensions and Measures
• Using Show Me!
• Tour of Shelves (How shelves and marks work)
• Building Basic Views
• Help Menu and Samples
• Saving and sharing your work
Unit 3: Analysis
• Creating Views
• Marks
• Size and Transparency
• Highlighting
• Working with Dates
• Date aggregations and date parts
• Discrete versus Continuous
• Dual Axis / Multiple Measures
• Combo Charts with different mark types
• Geographic Map Page Trails
• Heat Map
• Density Chart
• Scatter Plots
• Pie Charts and Bar Charts
• Small Multiples
• Working with aggregate versus disaggregate data
• Analyzing
• Sorting & Grouping
• Aliases
• Filtering and Quick Filters
• Cross-Tabs (Pivot Tables)
• Totals and Subtotals Drilling and Drill Through
• Aggregation and Disaggregation
• Percent of Total
• Working with Statistics and Trend lines
Unit 4: Getting Started with Calculated Fields
• Working with String Functions
• Basic Arithmetic Calculations
• Date Math
• Working with Totals
• Custom Aggregations
• Logic Statements
Unit 5: Formatting
• Options in Formatting your Visualization
• Working with Labels and Annotations
• Effective Use of Titles and Captions
• Introduction to Visual Best Practices
Unit 6: Building Interactive Dashboard
• Combining multiple visualizations into a dashboard
• Making your worksheet interactive by using actions and filters
• An Introduction to Best Practices in Visualization
/R_(programming_language)-Logo.wine.png?w=900&ssl=1){kind=logo}
Unit 1: Essential to R programming
• An Introduction to R
• Introduction to the R language
• Programming statistical graphics
• Programming with R
• Simulation
• Computational linear algebra
• Numerical optimization
Unit 2: Data Manipulation Techniques using R programming
• Data in R
• Reading and Writing Data
• R and Databases
• Dates
• Factors
• Subscribing
• Character Manipulation
• Data Aggregation
• Reshaping Data
Unit 3: Statistical Applications using R programming
• Basics
• The R Environment
• Probability and distributions
• Descriptive statistics and graphics
• One- and two-sample tests
• Regression and correlation
• Analysis of variance and the Kruskal–Wallis test
• Tabular data
• Power and the computation of sample size
• Advanced data handling
• Multiple Regression
• Linear models
• Logistic regression
• Survival analysis
• Rates and Poisson regression
• Nonlinear curve fitting
Data Structures
• Introduction to SAS interface and library structure and definition
• Reading data using Datalines and importing and exporting datasets
• Infiles statement – reading raw data
• Formats and Informats
• Variable attributes and data modification using Data and Set statements
Data Management
• Using conditional statements to modify data – Where, If and Nested IF
• Appending and Merging datasets
• SAS Functions for data manipulation
• Loops and Arrays in SAS
Report Generation
• Basic Proc steps – like Proc Contents
• Proc Format, Proc Report and Proc Tabulate
• Proc steps for basic statistics – like Proc Univariate and Proc Means
Advanced SAS
Proc SQL
• Introduction to SQL – basic DBMS and RDBMS concepts
• Using SQL Procedures in SAS
• Using conditional statements in SQL and aggregate functions
• Data manipulation using Proc SQL
SAS Macros
• Introduction to Macros
• Local and Global declarations
• Using built-in macro procedures and functions
