Course Overview
Data Science Master Program Training Institute in Electronic City Bangalore Overview
Let eMexo Technologies Best Data Science Master Program Training in Electronic City Bangalore take you from the fundamentals of Data Science to Advance Data Science and make you an expert in developing real-time Apache Spark applications. Here are the major topics we cover under this Data Science Master Program course Syllabus Introduction to Data Science, Introduction to Python, Python Basics, Python Packages, Importing Data, Manipulating Data, Statistics Basics, Error Metrics, Machine Learning, Supervised Learning, Unsupervised Learning, SVM, SVM Kernal, Other Machine Learning algorithms, Artificial Intelligence, AI Introduction, Deep Learning, Deep Learning Algorithms, Introduction to NLP, Text to Features (Feature Engineering), Tasks of NLP, Project Works, Tableau, Tableau Course Material, Learn Tableau Basic Reports, Learn Tableau Charts, Learn Tableau Advanced Reports, Learn Tableau Calculations & Filters, Learn Tableau Dashboards, Server, Oracle Database, Introduction to Oracle Database, Retrieve Data using the SQL SELECT Statement, Learn to Restrict and Sort Data, Usage of Single-Row Functions to Customize Output, Invoke Conversion Functions and Conditional Expressions, Aggregate Data Using the Group Functions, Display Data from Multiple Tables Using Joins, Use Subqueries to Solve Queries, The SET Operators, Data Manipulation Statements, Use of DDL Statements to Create and Manage Tables, Other Schema Objects, Control User Access, Management of Schema Objects, Manipulate Large Data Sets, Data Management in Different Time Zones, Retrieve Data Using Sub-queries, and Regular Expression Support. Each topic will be covered in a practical way with examples for our Data Science Master Program Course in Electronic City Bangalore.
All the topics will be covered with Practical and hands-on training. Our trainers have industry experience with live project experience in cutting-edge technologies which they teach. We hire only the Best Data Science Master Program industry specialists as trainers for our Data Science Master Program Certification Training in Electronic City Bangalore.
If you are looking for Data Science Master Program Certification Course in Electronic City Bangalore, eMexo Technologies is the Best Data Science Master Program Training Institute in Electronic City Bangalore. Come over to our training institute for a free demo class. Let our trainer give you a demo on Data Science Master Program and only then do you make the decision to enroll in the training program.
Data Science Master Program Course in Electronic City Bangalore Key Features
eMexo Technologies offers Best Data Science Master Program Course in Electronic City Bangalore with the TOP industry expert trainers. Here are the key features.
- Free Demo Class Available
- Practical Approach
- Expert & Certified Trainers
- High Quality Training
- 100% Job Oriented Training
- Real World use cases and Scenarios
- Completed 400+ Batches
- Certification Guidance
Why should you take Data Science Master Program Training in Electronic City Bangalore?
- Data Science Master Program course helps you to learn each and every fundamental details about Data Science.
- By taking our Data Science Master Program, you'll acquire expertise in data analytics, machine learning, and data visualization – skills highly valued by employers worldwide.
- The global spring market is estimated to be US $ 64.14 billion in 2021 and thrived at a CAGR of 29.0% from 2022 to 2029.
- Data Science is used by Microsoft, Amazon, Google, Walmart, IBM, Splunk, Wipro, Accenture, and many other MNCs around the world.
- According to Naukri their are 17000+ Data Science Job vacancies available in India.
- A Data Scientist annual salary is around $ 159,972 per annum according to Indeed.
Data Science Master Program Certification Training in Electronic City Bangalore Description:
This Data Science Master Program training course in Electronic City Bangalore is specifically designed for:
- Software Engineers
- Freshers
- System Administrators
- Analytics Professionals
- Big Data Professionals
- Project Manager
- Technical Leads
After completing the Data Science Master Program training course in Electronic City Bangalore, you will be expert in:
- Data Analytics and Visualization
- Machine Learning Algorithms
- Data Preprocessing and Cleaning
- Big Data Technologies
- Programming Languages
- Deep Learning and Neural Networks
- Natural Language Processing (NLP)
The Data Science Master Program Training Institute in Electronic City Bangalore does not require any prerequisites for taking a Data Science Master Program Certification Course in Electronic City Bangalore. The following skills are only considered as an additional benefit for studying the eMexo Technologies Data Science Master Program certification course.
- Basic Programming Knowledge
- Mathematics and Statistics Fundamentals
- Database Fundamentals
Don’t worry if you don’t have the above pre-requisites. Our experienced professional trainers will help each participant become a Data Science expert and reach their dream destination quickly through theoretical and hands-on training, real-time live projects and use cases.
Unlock the power of data with our Data Science Master Program Training Course in Electronic City Bangalore. Gain in-demand skills in data analytics, machine learning, and big data technologies. Harness the potential of data-driven insights to make informed business decisions. Stay ahead in the competitive job market with industry-recognized certifications. Enroll now and shape a rewarding career as a proficient data scientist with eMexo Technologies.
Data Science Master Program Certification
Data Science Master Program Certification
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Course Content
- Linear Regression
- Linear Equation
- Slope
- Intercept
- R square value
- Logistic regression
- ODDS ratio
- Probability of success
- Probability of failure Bias Variance Tradeoff
- ROC curve
- Bias Variance Tradeoff
- Hands-on: we’ve reviewed the main ways to approach the problem of modeling data using simple and definite
- K – Nearest Neighbour
- Naïve Bayes Classifier
- Decision Tree – CART
- Decision Tree – C50
- Random Forest
- Hands-on: We have covered the simplest but still very practical machine learning models in an eminently practical way to get us started on the complexity
- Hands-on: where we will cover several regression techniques, it will be time to go and solve a new type of problem that we have not worked on, even if it’s possible to solve the problem with clustering methods (regression), using new mathematical tools for approximating unknown values.
- Hands-on: In it, we will model past data using mathematical functions, and try to model new output based on those modeling.
- CNN – Convolutional Neural Network
- RNN – Recurrent Neural Network
- ANN – Artificial Neural Network
- Hands-on: We took a very important step toward solving complex problems together by means of implementing our first neural
- Hands-on: Now, the following architectures will have familiar elements, and we will be able to extrapolate the knowledge acquired in this chapter, into novel
- Text Classification
- Text Matching
- Levenshtein Distance
- Phonetic Matching
- Flexible String Matching
- Hands-on: provided, you will even be able to create new customized
- Hands-on: As our models won’t be enough to solve very complex problems, in the following chapter, our scope will expand even more, adding the important dimension of time to the set of elements included in our generalization.
- Overview: Visualizations
- Using visualizations
- Create a new report
- Create and arrange visualizations
- Format a visualization
- Create chart visualizations
- Use text, map, and gauge visualizations and save a report
- Use a slicer to filter visualizations
- Sort, copy, and paste visualizations
- Download and use a custom visual from the gallery
- Hands-On
- Modify and Print a Report
- Rename and delete report pages
- Add a filter to a page or report
- Set visualization interactions
- Print a report page
- Send a report to PowerPoint
- Create a Dashboard
- Create and manage dashboards
- Pin a report tile to a dashboard
- Pin a live report page to a dashboard
- Pin a tile from another dashboard
- Pin an Excel element to dashboard
- Manage pinned elements in Excel
- Add a tile to a dashboard
- Build a dashboard with Quick Insights
- Set a Featured (default) dashboard
- Ask Questions about Your Data
- Ask a question with Power BI Q&A
- Tweak your dataset for Q&A
- Enable Cortana for Power BI
- Hands-On
- Use Power BI Mobile Apps
- Get Power BI for mobile
- View reports and dashboards in the iPad app
- Use workspaces in the mobile app
- Sharing from Power BI Mobile
- Use Power BI Desktop
- Install and launch Power BI Desktop
- Get data
- Reduce data
- Transform data
- Relate tables
- Get Power BI Desktop data with the Power BI service
- Export a report from Power BI service to Desktop
- Hands-On
- Area Chart
- Bar Chart
- Box Plot
- Bubble Chart
- Bump Chart
- Bullet Graph
- Circle Views
- Dual Combination Chart
- Dual Lines Chart
- Funnel Chart
- Traditional Funnel Charts
- Gantt Chart
- Grouped Bar or Side by Side Bars Chart
- Heatmap
- Highlight Table
- Histogram
- Cumulative Histogram
- Line Chart
- Lollipop Chart
- Pareto Chart
- Pie Chart
- Scatter Plot
- Stacked Bar Chart
- Text Label
- Tree Map
- Word Cloud
- Waterfall Chart
- Hands-on: Create and use Static Sets
- Hands-on: Create and use Dynamic Sets
- Hands-on: Combine Sets into more Sets
- Hands-on: Use Sets as filters
- Hands-on: Create Sets via Formulas
- Hands-on: Control Sets with Parameters
- Hands-on: Control Reference Lines with Parameters
- Dual Axis Reports
- Blended Axis
- Individual Axis
- Add Reference Lines
- Reference Bands
- Reference Distributions
- Basic Maps
- Symbol Map
- Use Google Maps
- Mapbox Maps as a Background Map
- WMS Server Map as a Background Map
- Hands-on: Create Barcharts
- Hands-on: Create Area Charts
- Hands-on: Create Maps
- Hands-on: Create Interactive Dashboards
- Hands-on: Create Storylines
- Hands-on: Understand Types of Joins and how they work
- Hands-on: Work with Data Blending in Tableau
- Hands-on: Create Table Calculations
- Hands-on: Work with Parameters
- Hands-on: Create Dual Axis Charts
- Hands-on: Create Calculated Fields
- Calculated Fields
- Basic Approach to Calculate Rank
- Advanced Approach to Calculate Ra
- Calculating Running Total
- Filters Introduction
- Quick Filters
- Filters on Dimensions
- Conditional Filters
- Top and Bottom Filters
- Filters on Measures
- Context Filters
- Slicing Filters
- Data Source Filters
- Extract Filters
- Hands-on: Creating Data Extracts in Tableau
- Hands-on: Understand Aggregation, Granularity, and Level of Detail
- Hands-on: Adding Filters and Quick Filters
- Excel tutorial
- Text to Columns
- Concatenate
- The Concatenate Function
- The Right Function with Concatenation
- Absolute Cell References
- Data Validation
- Time and Date Calculations
- Conditional Formatting
- Exploring Styles and Clearing Formatting
- Using Conditional Formatting to Hide Cells
- Using the IF Function
- Changing the “Value if false” Condition to Text
- Pivot Tables
- Creating a Pivot Table
- Specifying PivotTable Data
- Changing a PivotTables Calculation
- Filtering and Sorting a PivotTable
- Creating a PivotChart
- Grouping Items
- Updating a PivotTable
- Formatting a PivotTable
- Using Slicers
- Charts
- Creating a Simple Chart
- Charting Non-Adjacent Cells
- Creating a Chart Using the Chart Wizard
- Modifying Charts
- Moving an Embedded Chart
- Sizing an Embedded Chart
- Changing the Chart Type
- Chart Types
- Changing the Way Data is Displayed
- Moving the Legend
- Formatting Charts
- Adding Chart Items
- Formatting All Text
- Formatting and Aligning Numbers
- Formatting the Plot Area
- Formatting Data Markers
- Pie Charts
- Creating a Pie Chart
- Moving the Pie Chart to its Own Sheet
- Adding Data Labels
- Exploding a Slice of a Pie Chart
- Data Analysis − Overview
- types of Data Analysis
- Data Analysis Process
- Working with Range Names
- Copying Name using Formula Autocomplete
- Range Name Syntax Rules
- Creating Range Names
- Creating Names for Constants
- Managing Names
- Scope of a Name
- Editing Names
- Applying Names
- Using Names in a Formula
- Viewing Names in a Workbook
- Copying Formulas with Names
- Difference between Tables and Ranges
- Create Table
- Table Name
- Managing Names in a Table
- Table Headers replacing Column Letters
- Propagation of a Formula in a Table
- Resize Table
- Remove Duplicates
- Convert to Range
- Table Style Options
- Table Styles
- Cleaning Data with Text Functions
- Removing Unwanted Characters from Text
- Extracting Data Values from Text
- Formatting Data with Text Functions
- Date Formats
- Conditional Formatting
- Sorting
- Filtering
- Lookup Functions
- Pivoting
- Hands-On
- Introduction to Probability
- Probability Addition Rule
- Probability Multiplication Rule
- Distributions
- Correlation
- Regression
- Hypothesis Testing
- ANOVA and Chi-Square Tests
- Data Cleaning
- Imputation Techniques
- Measure Of central tendency, Measures of Dispersion
- Graphical Techniques, Skewness & Kurtosis, Box Plot
- Descriptive Stats
- Central Limit Theorem, Confidence interval
- Hands-On
- Fundamentals of SQL Syntax and Statements
- Data Filtering and Sorting Techniques
- Utilization of Single-Row Functions
- Aggregate and Group Functions
- Analytical (Window) Functions
- Data Definition Language (DDL) – Creating and Managing Schema Objects
- Data Manipulation Language (DML) – Inserting, Updating, and Deleting Data
- Implementation of Data Constraints
- Set Operations – UNION, INTERSECT, and MINUS
- Subqueries and Nested Queries
- Joins and Multi-Table Queries
- Transaction Control Language (TCL) – COMMIT, ROLLBACK, SAVEPOINT
- Data Control Language (DCL) – GRANT and REVOKE Permission
