Data Analytics Certification Training

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4627 Reviews 4.9

Learners : 1080

Duration:   30 Days

About Course

Data analytics is a discipline that is always changing. Your foundation is quickly built upon by this course. These fundamental tools and approaches help you make successful decisions quickly, whether you’re planning your entire business intelligence strategy or conducting your own research. In this brisk introductory class, we’ll look at the background of business intelligence, how it relates to data analysis, and why the two are necessary to support organizations in assembling the “data puzzle” completely. We’ll discuss the challenges teams encounter when dealing with data overload and offer some potential fixes.

Data Analytics Training Course Syllabus

Introduction to Python

✔ Why Python for Machine Learning
✔ Installing Python
✔ Python IDE’s
✔ Writing the First Python Programme
✔ Executing of Python programs

Data Types in Python (Data Analytics)

✔ Integer
✔ Float
✔ String
✔ Bool

Operators in Python

✔ Relational Operators
✔ Arithmetic Operators
✔ Logical Operators
✔ Concatenation Operator

Python Objects (Data Analytics)

✔ Lists
✔ Tuples
✔ Sets
✔ Dictionaries
✔ Range

Control Flow and Loops

✔ If and else if statements
✔ For and while Statements
✔ Iterables and Iterators
✔ List Comprehensions and Generator

Functions in Pythons (Data Analytics)

✔ Writing user-defined functions
✔ Lambda Functions
✔ Using *args and *kwargs

Error handling in Python

✔ Handling Errors in Python
✔ Types of Errors
✔ Using try and except
✔ Raising an Error

Python Modules

✔ Usage of Modules
✔ Datetime
✔ Re
✔ OS
✔ Numpy
✔ Pandas
✔ Matplotlib • Seaborn
✔ scikit-learn
✔ sklearn and many more

Working with Files

✔ File Input/output
✔ Opening of Files
✔ Reading Information from Files
✔ Writing to a File

Importing Data in Python

✔ Csv Files
✔ Excel Sheets
✔ SAS Files
✔ From Web
✔ Working with Relational Databases
✔ Using API’s

Cleaning Data in Python

✔ 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

Manipulating Data Frames with Pandas

✔ Extracting and Transforming Data
✔ Advanced Indexing
✔ Re-arranging and Re-shaping of data
✔ Grouping Data

Merging Data Frames with Pandas

✔ Preparing Data
✔ Concatenating Data
✔ Merging Data

Introduction to Data Visualization

✔ Customizing plots
✔ Plotting 2D arrays
✔ Statistical Plotting using Seaborn
✔ Analyzing Time series and Images

Data Visualization using Bokeh

✔ Basic Plotting with Bokeh
✔ Layouts, Interactions and Annotations
✔ Building Interactive Apps with Bokeh

Regular Expressions in Python

✔ 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



Coming Soon



5th NOV 2022



Coming Soon



Don't find suitable time ?


Live Virtual Training

  • Schedule your sessions at your comfortable timings.
  • Instructor-led training, Real-time projects
  • Certification Guidance.

Self-Paced Learning

  • Complete set of live-online training sessions recorded videos.
  • Learn technology at your own pace.
  • Get access for lifetime.

Corporate Training

  • Learn As A Full Day Schedule With Discussions, Exercises,
  • Practical Use Cases
  • Design Your Own Syllabus Based
For Business

Data Analytics Training FAQ'S

What are the key requirements for becoming a Data Analyst?

These are typical data science interview questions that are regularly asked by interviewers to gauge how well you understand the necessary qualifications. Your understanding of the competencies needed to become a data scientist will be tested by this data analyst interview question.

Get ahead in your career by learning Data Analytics through VISWA Online Trainings

Name the best tools used for data analysis.

You’ll typically discover a question about the most popular tool in any data analytics interview questions. These behavioural interview questions for data analysts and data scientists are designed to gauge your understanding of the subject and depth of expertise. Only candidates with a wealth of practical experience will perform well on this question. Therefore, prepare for your analyst interview by practising tools and analytics questions as well as data analyst behavioural interview questions.

The most useful tools for data analysis are:

  • Tableau
  • Google Fusion Tables
  • Google Search Operators
  • RapidMiner
  • Solver
  • OpenRefine
  • NodeXL
  • io
  • Apache Spark
  • R Programming
  • SAS
  • Python
  • Microsoft Power BI
  • TIBCO Spotfire
  • Qlik
  • Google Data Studio
  • Jupyter Notebook
  • Looker
  • Domo
Define Outlier

Without this query, a list of interview questions and solutions for data analysts would be incomplete. Data analysts frequently use the term “outlier” to describe a number in a sample that appears to be significantly different from the norm.The outlier values are significantly different from the data sets. These might be smaller or bigger, but they would be offset from the primary data points. These outlier values may exist for a variety of causes, including measurement errors and others.Two types of outliers exist.

What is K-mean Algorithm?

Using the K-mean partitioning technique, objects are divided into K groups. The clusters in this approach are spherical, the data points are oriented around each cluster, and the cluster variances are similar to one another. Since it already knows the clusters, it computes the centroids. By identifying the different types of groupings, it supports the business’s presumptions. It is helpful for a variety of reasons, including its ability to handle big data sets and ease of adaptability to new examples.

How should you tackle multi-source problems?

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.


Vishnu Gadipudi
Vishnu Gadipudi
I Enrolled in VISWA Online Trainings for IBM Integration BUS course . Recently I Completed IBM Integration BUS Batch. It was Really Awesome Experience. Best Place To Learn , Experienced Trainer, Gives Us High Level Knowledge....
Navya Biradavolu
Navya Biradavolu
I was enrolled for looker Bl Tool,it was amazing experience . especially soft skill batch is one of my favourite batch . overall learning process is quite impressive.
Indla sneha
Indla sneha
I have joined I have joined VISWA Online TRAININGS for Java full stack course and i have completed Advance Java module. I had a good knowledge of Hibernate, spring,spring boot,spring MVC. Tutor has knowledge in depth and is supportive. Srinadh sir solved all our doubts....
bindu hima
bindu hima
I am recently completed Talend course and trainer is Rajendra very professional and helpful. All the doubts were solved in a precise manner.
Tarunasree Gowra
Tarunasree Gowra
"I truly enjoyed this course." Chaitanya sir fantastic-very knowledgeable. Sir give us very informative and clear instruction on how to achieve the goal. Thank you!
Tejaswini Kommu
Tejaswini Kommu
Overall Linux Admin sessions batch was very good. Mr. RAM Krishna teaching was very helpful to remind our basic concepts in linux & networking.
Gopanaboina Mounika
Gopanaboina Mounika
It was great learning with such a great and experienced staff. Praveen Sir (Oracle EPM Cloud - FCCS) was very helpful and operations team also very helpful in solving any minor problems students go through process.
Jyothi Gutlapalli
Jyothi Gutlapalli
I like to share my experience which provide lots of courses and one of those I recently completed my Salesforce BA Course and I like to tell you it was a great experience and my knowledge and confidence is really boosted after completing this course.
Good experience and great learning platform for Hyperion Essbase and Planning. The faculty is also well trained and soft spoken.
Chaitu Viswa
Chaitu Viswa
It was very good session for QlikView. I would like to thank to teacher Mr.Chandu for providing guidance for the required modules. Thanks VISWA Team for giving apportunity to leran new skills.

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