Data Analytics Course

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 Course Kochi

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

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

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Master in Data Analytics

What you’ll learn

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

  • Power Bi
  • Tableau
  • MonkeyLearn
  • RapidMiner
  • R
  • Predictive Data Analytics
  • Diagnostic Data Analytics
  • Descriptive Data Analytics
  • Prescriptive 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.
  • Mathematical skills
  • Statistics
  • Knowledge of the domain
  • Machine learning
  • Python
  • Data visualization

Technologies that use Data Science