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
Your certification towards a successful career.
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Course Content
Python Basics
- Python Basic Data types
- Lists
- Slicing
- IF statements
- Loops
- Dictionaries
- Tuples
- Functions
- Array
- Selection by position & Labels
- Hands-on: Practice and Quickly learn Python necessary skills by solving simple questions and problems.
- Hands-on: How Python uses indentation to structure a program, and how to avoid some common indentation errors.
- Hands-on: You executed to make simple numerical lists, as well as a few operations you can perform on numerical lists, tuples, dictionaries, and set
Importing Data
- Reading CSV files
- Saving in Python data
- Loading Python data objects
- Writing data to CSV file
- Hands-on: To generate data sets and create visualizations of that data. You learned to create simple plots with Matplotlib, and you saw how to use a scatter plot to explore random
- Hands-on: You learned to create a histogram with Pygal and how to use a histogram to explore the results of rolling dice of different
- Hands-on: Generating your own data sets with code is an interesting and powerful way to model and explore a wide variety of real-world
- Hands-on: As you continue to work through the data visualization projects that follow, keep an eye out for situations you might be able to model with
Manipulating Data
- Selecting rows/observations
- Rounding Number
- Selecting columns/fields
- Merging data
- Data aggregation
- Data munging techniques
- Hands-on: As you gain experience with CSV and JSON files, you’ll be able to process almost any data you want to analyze.
- Hands-on: Most online data sets can be downloaded in either or both of these From working with these formats, you’ll be able to learn other data formats as well.
Statistics Basics
- Central Tendency
- Mean
- Median
- Mode
- Skewness
- Normal Distribution
- Probability Basics
- What does it mean by probability?
- Types of Probability
- ODDS Ratio?
- Standard Deviation
- Data deviation & distribution
- Variance
- Bias variance Tradeoff
- Underfitting
- Overfitting
- Distance metrics
- Euclidean Distance
- Manhattan Distance
- Outlier analysis
- What is an Outlier?
- Inter Quartile Range
- Box & whisker plot
- Upper Whisker
- Lower Whisker
- Scatter plot
- Cook’s Distance
- Missing Value Treatment
- What is NA?
- Central Imputation
- KNN imputation
- Dummification
- Correlation
- Pearson correlation
- Positive & Negative correlation
- Hands-on: Compute probability in a situation where there are equally-likely outcomes
- Hands-on: Apply concepts to cards and dice
- Hands-on: Compute the probability of two independent events both occurring
- Hands-on: Compute the probability of either of two independent events occurring
- Hands-on: Do problems that involve conditional probabilities
- Hands-on: Calculate the probability of two independent events occurring
- Hands-on: List all permutations and combinations
- Hands-on: Apply formulas for permutations and combinations
Error Metrics
- Classification
- Confusion Matrix
- Precision
- Recall
- Specificity
- F1 Score
- Regression
- MSE
- RMSE
- MAPE
- Hands-on: State why the z’ transformation is necessary
- Hands-on: Compute the standard error of z
- Hands-on: Compute a confidence interval on ρ The computation of a confidence interval
- Hands-on: Estimate the population proportion from sample proportions
- Hands-on: Apply the correction for continuity
Supervised Learning
- 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
Other Machine Learning algorithms
- 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.
Deep Learning Algorithms
- 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
Tasks of NLP
- 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.
Learn Tableau Charts
- 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
Learn Tableau Advanced Reports
- 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
Learn Tableau Calculations & Filters
- 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
Introduction to Oracle Database
- List the features of Oracle Database 11g
- Discuss the basic design, theoretical, and physical aspects of a relational database
- Categorize the different types of SQL statements
- Describe the data set used by the course
- Log on to the database using the SQL Developer environment
- Save queries to files and use script files in SQL Developer
- Hands-on: Prepare your environment
- Hands-on: Work with Oracle database tools
- Hands-on: Understand and work with language features
Retrieve Data using the SQL SELECT Statement
- List the capabilities of SQL SELECT statements
- Generate a report of data from the output of a basic SELECT statement
- Select All Columns
- Select Specific Columns
- Use Column Heading Defaults
- Use Arithmetic Operators
- Understand Operator Precedence
- Learn the DESCRIBE command to display the table structure
- Hands-on: Individual statements in SQL scripts are commonly terminated by a line break (or carriage return) and a forward slash on the next line, instead of a semicolon.
- Hands-on: You can create a SELECT statement, terminate it with a line break, include a forward slash to execute the statement, and save it in a script file.
Learn to Restrict and Sort Data
- Write queries that contain a WHERE clause to limit the output retrieved
- List the comparison operators and logical operators that are used in a WHERE clause
- Describe the rules of precedence for comparison and logical operators
- Use character string literals in the WHERE clause
- Write queries that contain an ORDER BY clause to sort the output of a SELECT statement
- Sort output in descending and ascending order
- Hands-on: Creating the queries in a compound query must return the same number of columns.
- Hands-on: Create corresponding columns in each query that must be of compatible data types.
- Hands-on: ORDER BY; it is, however, permissible to place a single ORDER BY clause at the end of the compound query
Usage of Single-Row Functions to Customize Output
- Describe the differences between single-row and multiple-row functions
- Manipulate strings with character functions in the SELECT and WHERE clauses
- Manipulate numbers with the ROUND, TRUNC, and MOD functions
- Perform arithmetic with date data
- Manipulate dates with the DATE functions
- Hands-on: Creating the distinction is made between single-row functions, which execute once for each
- Hands-on: row in a dataset, and multiple-row functions, which execute once for all the rows in a data- set.
Invoke Conversion Functions and Conditional Expressions
- Describe implicit and explicit data type conversion
- Use the TO_CHAR, TO_NUMBER, and TO_DATE conversion functions
- Nest multiple functions
- Apply the NVL, NULLIF, and COALESCE functions to the data
- Use conditional IF THEN ELSE logic in a SELECT
- Hands-on: we create and discuss the NVL function, which provides a mechanism to convert null values into more arithmetic-friendly data values.
Aggregate Data Using the Group Functions
- Use the aggregation functions in SELECT statements to produce meaningful reports
- Divide the data into groups by using the GROUP BY clause
- Exclude groups of date by using the HAVING clause
- Hands-on: Group functions operate on aggregated data and return a single result per group.
- Hands-on: These groups usually consist of zero or more rows of data.
The SET Operators
- Describe the SET operators
- Use a SET operator to combine multiple queries into a single query
- Control the order of rows returned
- Hands-on: Create The queries in the compound query must return the same number of columns.
- Hands-on: creating The corresponding columns must be of compatible data type.
- Hands-on: creating The set operators have equal precedence and will be applied in the order they are specified.
Data Manipulation Statements
- Describe each DML statement
- Insert rows into a table
- Change rows in a table by the UPDATE statement
- Delete rows from a table with the DELETE statement
- Save and discard changes with the COMMIT and ROLLBACK statements
- Explain read consistency
- Hands-on: Expressions and create expose a vista of data manipulation possibilities through the interaction of arithmetic and character operators with column or literal data, or a combination of the two.
Management of Schema Objects
- Add, Modify, and Drop a Column
- Add, Drop, and Defer a Constraint
- How to enable and Disable a Constraint?
- Create and Remove Indexes
- Create a Function-Based Index
- Perform Flashback Operations
- Create an External Table by Using ORACLE_LOADER and by Using ORACLE_DATAPUMP
- Query External Tables
- Hands-on: Create the function-based index and types.
Manage Objects with Data Dictionary Views
- Explain the data dictionary
- Use the Dictionary Views
- USER_OBJECTS and ALL_OBJECTS Views
- Table and Column Information
- Query the dictionary views for constraint information
- Query the dictionary views for view, sequence, index, and synonym information
- Add a comment to a table
- Query the dictionary views for comment information
Manipulate Large Data Sets
- Use Subqueries to Manipulate Data
- Retrieve Data Using a Subquery as Source
- Insert Using a Subquery as a Target
- Usage of the WITH CHECK OPTION Keyword on DML Statements
- List the types of Multitable INSERT Statements
- Use Multitable INSERT Statements
- Merge rows in a table
- Track Changes in Data over a period of time
Regular Expression Support
- Use the Regular Expressions Functions and Conditions in SQL
- Use Meta Characters with Regular Expressions
- Perform a Basic Search using the REGEXP_LIKE function
- Find patterns using the REGEXP_INSTR function
- Extract Substrings using the REGEXP_SUBSTR function
- Replace Patterns Using the REGEXP_REPLACE function
- Usage of Sub-Expressions with Regular Expression Support
- Implement the REGEXP_COUNT function
- Hands-on: Expressions and create regular columns may be aliased using the AS keyword or by leaving a space between the column or expression and the alias. In this way, both wildcard symbols can be used as either specialized or regular characters in different segments of the same character string.
FAQs
At eMexo, we believe that there is nothing better than hands-on practice when it comes to learning concepts. our teaching method is 100% practical. You learn a concept, you practice it then and there with the trainer. It also provides assignments for each topic that you can practice at home so that questions about the topic can be clarified to the trainer the next day.
All of our instructors are industry experts hired by top companies and have hands-on experience with JAVA.
Our trainers are expert professionals in their organizations and they often act as the interviewer to hire new candidates. Our trainers will help you prepare your resume with industry standards. After all, they know exactly what to look in a resume.
Our trainers are professionals working in multinational corporations. They are experts in their field and they know exactly what the interviewer will look for in the candidate. Experienced trainers not only share interview questions but also conduct mock interviews to help prepare for the actual interview.
If you miss a class the content of that class will be taught to you again. With us, you might miss a class but not the content.
Yes, we provide fast-track training as well for those who want to complete the course faster. The curriculum and the total hours required to complete the course will remain the same. However, the trainer will be spending more hours with you to complete the course.
We provide both regular and weekend training. Talk to our training partner to learn more about the timing.
Yes, at the end of training we provide a certification of completion.
Yes, absolutely! Talk to our training counselor by phone at +91-9513216462 or email us at info@emexotechnologies.comtoarrangeforafreedemo.Youcanalsofillinthecontactus form below and we will call you to discuss your training requirements.
Please contact our course advisor at +91-9513216462 or you can share your queries through info@emexotechnologies.com
