Data Analytics Course

Master in Data Analytics

Updated Syllabus 2023

Data Analytics course from SMEClabs will make you an expert in Data analytics. Learn about the different strategies and tools in Data analytics. During this course, you will acquire several in-demand skills which will be really useful while applying for a job in Data analytics. We have included all the relevant topics regarding the data analyses. You will be able to collect, transform, and organize the data from junk data. Prepare yourself for a high-paying job and grab the opportunity to connect with top employers.”Best Data Analytics course Kochi 2023 updated syllabus. Tools such as Python, R, Power BI, and Tableau are used for Data visualization Training”

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Data Analytics Courses

Master in Data Analytics

Difficulty - Beginner / No experience | Eligibility - Any Degree, Diploma, Graduates | Mode - Offline - 240 Hours / OnDemand / Hybrid
Detailed Syllabus | Enroll Now

Master in Data Analytics Level Requirements:

Syllabus for Data Analytics Course - Master Level

Learn Python Program from Scratch

Course Introduction
Programming

Statistical and Mathematical Essential for Data Science

Introduction
Sample or Population Data?
The Fundamentals of Descriptive Statistics
Measures of Central Tendency, Asymmetry, and Variability
Practical Example: Descriptive Statistics
Distributions
Estimators and Estimates
Confidence Intervals Lesson
Practical Example: Inferential Statistics
Hypothesis Testing: Introduction
Practical Example: Hypothesis Testing
The Fundamentals of Regression Analysis
Assumptions for Linear Regression Analysis
Dealing with Categorical Data
Practical Example: Regression Analysis

Data Science with Python

Python Basics
Python Data Structures
Python Programming Fundamentals
Working with Data in Python
Data Science Overview
Data Analytics Overview
Statistical Analysis and Business Applications
Python Environment Setup and Essentials
Mathematical Computing with Python (NumPy)
Data Manipulation with Pandas
Machine Learning with Scikit–Learn
Natural Language Processing with Scikit Learn
Data Visualization in Python using Matplotlib
Web Scraping with Beautiful Soup
Working with NumPy Arrays

Machine Learning

Introduction to Artificial Intelligence and Machine Learning
Data Wrangling and Manipulation
Supervised Learning
Feature Engineering
Supervised Learning Classification
Unsupervised Learning
Time Series Modeling
Ensemble Learning
Recommender Systems
Text Mining

AI (Natural Language Processing)

Introduction to Artificial Intelligence and Machine Learning in NLP
Perform various Text Analysis, Summarization and Extraction, Sentiment Mining, Text Classification, Text Summarization, Information Extraction etc.
Create a basic speech recognizer to convert speech to text
Perform advanced Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition
Implement emotion recognition/sentiment analysis etc. using real time speech recognitions.

Database

Introduction to SQL
Database Normalization and Entity-Relationship (ER) Mode
Installation configurations to setup MySQL
Understanding Database and Tables
Learn Operators, Constraints, and Data Types
Understanding functions, Subqueries, Operators, and Derived Tables in SQL

Data Science with R

Introduction to Business Analytics
Formatting Conditional Formatting and Important Functions
Analyzing Data with Pivot Tables
Dashboarding
Business Analytics with Excel
Data Analysis Using Statistics

Visualization with Tableau

Learn to perform data visualization from scratch from installation to data loading and interface bring up
Understanding Discrete and Continuous values and applications
Aggregations in tableau
Creating Charts in Tableau Bar Char, Line Chart, Scatter Plots, Dual-Axis Charts Combined-Axis Charts, Funnel Chart, Cross Tabs Highlight, Tables Maps
Understanding data and various techniques to rename, Hide, Sort Columns and field properties
Learn basics of Filters in Tableau
Performing data Analytics in sheets
Creating interactive Dashboards in Tableau

Visualization with Power BI

Understand various data streams or sources, and implement the pipeline into Power BI
Exploring various functionalities and understand data patterns
Create custom dashboards to various projects
Creating an Analysis or Management Reports.

Big Data Analytics

Introduction to Hadoop, Architecture, Administration and Components
Understanding NoSQL Databases HBase
Understand basic object-oriented programming methodologies in Scala
Introduction to Scala, Basics of Functional Programming, Case Objects and Classes Collections
Introduction to Spark, Work with RDD in Apache Spark, processing real time data
Perform DataFrame operations in Spark using SQL queries
Spark MLib Modelling Big Data with Spark
Introduction to Spark GraphX

Virtual Lab Facilities

India’s first automation V-lab 50000 Sqft.

Corporate Training On-site/Online

Successfully Completed 1200+ Companies

Campus Workshop

Successfully Completed 2000+ Colleges

Internship

Successfully Completed 10000+ Students

On Job Training

Successfully Completed 500+ Students

Data Analytics Training Center

We also have a branch in Infopark kochi.

Practical only subscription

We have several clients, and also we have been part of several international projects.

Classroom Data Science Course

Candidates who perform well will be recruited to our Infopark branch.

Flexible Schedule

Set and maintain flexible deadlines.

Trusted by genius people.

SMEClabs have paved the way for several candidates to get their dream job.

What you’ll learn

Solve any data analytics problem using R and Python
Perform Logistic Regression using Cancer remission data set.
Linear regression in python
Data visualization in R-Bar graphs,Stacked bar,grouped bar graph,Line chart for time series data,Box plot to calculate mean, median, min ,max ,3rd quartile and 1st quartile values
Basics of Python,importing sys library,platform,checking the platform,run a code,checking data type,performing calculations,concatenating of strings,conversion of values,working on tuples,
Data mapping and indexing using enumerate,creating dictionaries using enumerate,sorting without order,reversing the list,append the list.
Mathematical on Array using Numpy,decalring the 2D array,3D array,dtype,numpy operations,boolean array
Vector operation with data alignment,creating data frame out of dictionary of equal length list,create Data frame by combining two series,create Data frame from array.
Perform Data exploratory functions,importing and exporting the data sets,Data manipulation
Data manipulation in R-Dply,Filter, multiple filter, mutate, arrange, summarize etc

Why should you choose a Career Data Analytics?

Job Opportunities

Key Features

Get job-ready skills for Data Analytics from SMEClabs

You will be trained by professionals so you can acquire several data analytics skills such as Data cleansing, Data Visualization, Data Analysis with Python, etc. You will be part of several industry-relevant projects and also you will be part of several case studies. Learn about several data analytics tools and techniques such as Power BI, Tableau, R programming, Spreadsheets, etc. Understand how to collect the required data for an organization by getting industrial exposure by being part of our live projects with industrial relevance. We have an efficient placement assistance team to guide you in your career. Be able to get information from raw data.

FAQ - Frequently Asked Questions

What are the major tools in Data Analytics?

Power Bi
Tableau
MonkeyLearn
RapidMiner
KNIME
R

What are the major types of Data Analytics?

Predictive Data Analytics
Diagnostic Data Analytics
Descriptive Data Analytics
Prescriptive Data Analytics

Why should you choose a career in Data Analytics?

There are several opportunities in Data Analytics we can see data analytics professionals in the different industrial sectors. Most organizations are using data for their business operations, so there are a lot of opportunities in this sector. This is a high-paying job and also it provides good career growth too.

What are the major skills required for Data Analytics?

Mathematical skills
Statistics
Knowledge of the domain
Machine learning
Python
Data visualization

Technologies that use Data Science

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