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Data Analytics Training
Viswa Online Trainings is one of the world’s leading online IT training providers. We deliver a comprehensive catalog of courses and online training for freshers and working professionals to help them achieve their career goals and experience our best services.
Learners : 1080
About Course
Our Data analytics course are evolving disciplines. This class quickly equips you with that foundation. Whether you’re charting your overall business intelligence strategy or performing analysis yourself, these basic tools and techniques rapidly inform effective decision-making. In this fast-paced introductory workshop, we’ll examine the history of business intelligence, its relationship to data analysis, and why the two are needed to help businesses deliver a complete assembly of the ‘data puzzle’. We’ll also address hurdles teams face when dealing with data overload and suggests some possible solutions.
Data Analytics Training Course Syllabus
✔ Why Python for Machine Learning
✔ Installing Python
✔ Python IDE’s
✔ Writing the First Python Programme
✔ Executing of Python programs
✔ Integer
✔ Float
✔ String
✔ Bool
✔ Relational Operators
✔ Arithmetic Operators
✔ Logical Operators
✔ Concatenation Operator
✔ Lists
✔ Tuples
✔ Sets
✔ Dictionaries
✔ Range
✔ If and else if statements
✔ For and while Statements
✔ Iterables and Iterators
✔ List Comprehensions and Generator
✔ Writing user-defined functions
✔ Lambda Functions
✔ Using *args and *kwargs
✔ Handling Errors in Python
✔ Types of Errors
✔ Using try and except
✔ Raising an Error
✔ Usage of Modules
✔ Datetime
✔ Re
✔ OS
✔ Numpy
✔ Pandas
✔ Matplotlib • Seaborn
✔ scikit-learn
✔ sklearn and many more
✔ File Input/output
✔ Opening of Files
✔ Reading Information from Files
✔ Writing to a File
✔ Csv Files
✔ Excel Sheets
✔ SAS Files
✔ From Web
✔ Working with Relational Databases
✔ Using API’s
✔ Exploring the data
✔ Tidying Data for Analysis
✔ Combining Data
✔ Cleaning data
✔ Working with Numpy Arrays
✔ Creating and Manipulating Numpy Arrays
✔ Mathematical and Statistical Functions
✔ Subsetting Numpy Arrays
✔ Concatenating Numpy Arrays
✔ Pandas Foundations
✔ Data Ingestion and Inspection
✔ Exploratory Data Analysis
✔ Time Series in Pandas
✔ Extracting and Transforming Data
✔ Advanced Indexing
✔ Re-arranging and Re-shaping of data
✔ Grouping Data
✔ Preparing Data
✔ Concatenating Data
✔ Merging Data
✔ Customizing plots
✔ Plotting 2D arrays
✔ Statistical Plotting using Seaborn
✔ Analyzing Time series and Images
✔ Basic Plotting with Bokeh
✔ Layouts, Interactions and Annotations
✔ Building Interactive Apps with Bokeh
✔ Basic concepts of String Manipulations
✔ Formatting Strings
✔ Pattern Matching
✔ Advance Regular Expressions
| Live Instructor Based Training With Software |
| Lifetime access and 24×7 support |
| Certification Oriented content |
| Hands-On complete Real-time training |
| Get a certificate on course completion |
| Flexible Schedules |
| Live Recorded Videos Access |
| Study Material Provided |
Data Analytics Training - Upcoming Batches
7th NOV 2022
8 AM IST
Coming Soon
AM IST
5th NOV 2022
8 AM IST
Coming Soon
AM IST
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Certification Guidance.
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Complete set of live-online training sessions recorded videos.
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Learn As A Full Day Schedule With Discussions, Exercises,
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Design Your Own Syllabus Based
Data Analytics Training FAQ'S
These are standard data science interview questions frequently asked by interviewers to check your perception of the skills required. This data analyst interview question tests your knowledge about the required skill set to become a data scientist.
Get ahead in your career by learning Data Analytics through VISWA Online Trainings
A question on the most used tool is something you’ll mostly find in any data analytics interview questions. Such data science interview questions and data analyst behavioral interview questions are intended to test your knowledge and practical comprehension of the subject. Candidates with ample practical knowledge are the only ones to excel in this question. So make sure to practice tools and analytics questions for your analyst interview and data analyst behavioral interview questions
The most useful tools for data analysis are:
- Tableau
- Google Fusion Tables
- Google Search Operators
- KNIME
- RapidMiner
- Solver
- OpenRefine
- NodeXL
- io
- Apache Spark
- R Programming
- SAS
- Python
- Microsoft Power BI
- TIBCO Spotfire
- Qlik
- Google Data Studio
- Jupyter Notebook
- Looker
- Domo
A data analyst interview question and answers guide will not be complete without this question. An outlier is a term commonly used by data analysts when referring to a value that appears to be far removed and divergent from a set pattern in a sample. The outlier values vary greatly from the data sets. These could be either smaller, or larger but they would be away from the main data values. There could be many reasons behind these outlier values such as measurement, errors, etc. There are two kinds of outliers
K-mean is a partitioning technique in which objects are categorized into K groups. In this algorithm, the clusters are spherical with the data points are aligned around that cluster, and the variance of the clusters is similar to one another. It computes the centroids assuming that it already knows the clusters. It confirms the business assumptions by finding which types of groups exist. It is useful for many reasons, first of all, because it can work with large data sets and is easily accommodative to the new examples.
Multi-source problems are a group of computational data composed of dynamic, unstructured, and overlapping data that is hard to go through or obtain patterns from. To tackle multi-source problems, you need to:
- Identify similar data records and combine them into one record that will contain all the useful attributes, minus the redundancy.
- Facilitate schema integration through schema restructuring.
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