DATA ANALYTICS CERTIFICATION COURSE TRAINING
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- No-code course, Excel, MySQL, Tableau & Power BI
- 4 months program with 200+ learning hours
- 1 Client/live project with internship experience certificate
Accredited by
Instructor Led Live Online
Self Learning + Live Mentoring
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MODULE 1: DATA ANALYSIS FOUNDATION
• Data Analysis Introduction
• Data Preparation for Analysis
• Common Data Problems
• Classification of Analytics
• Various Tools for Data Analysis
MODULE 2: TIME SERIES AND TREND ANALYSIS
• Introduction to Time Series Data
• Preparing data for Time Series Analysis
• Types of Trends
• Trend Analysis of the Data with Excel
• Insights from Trend Analysis
• Hands-on Case Study: Trend Analysis
MODULE 3: RANKING ANALYSIS
• Introduction to Ranking Analysis
• Data Preparation for Ranking Analysis
• Performing Ranking Analysis with Excel
• Insights for Ranking Analysis
• Hands-on Case Study: Ranking Analysis
MODULE 4: VARIANCE AND FREQUENCY ANALYSIS
• Concept of Variability and Variance
• Data Preparation for Variance Analysis
• Business use cases for Variance and Frequency Analysis
• Performing Variance and Frequency Analysis
• Hands-on case study 1: Variance Analysis
• Hands-on case study 2: Frequency Analysis
MODULE 1: DATA SCIENCE ESSENTIALS
• Introduction to Data Science
• Data Science Terminologies
• Classifications of Analytics
• Data Science Project workflow
MODULE 2: DATA ENGINEERING FOUNDATION
• Introduction to Data Engineering
• Data engineering importance
• Ecosystems of data engineering tools
• Core concepts of data engineering
MODULE 3: PYTHON FOR DATA ANALYSIS
• Introduction to Python
• Python Data Types, Operators
• Flow Control statements, Functions
• Structured vs Unstructured Data
• Python Numpy package introduction
• Array Data Structures in Numpy
• Array operations and methods
• Python Pandas package introduction
• Data Structures : Series and DataFrame
• Pandas DataFrame key methods
MODULE 4: VISUALIZATION WITH PYTHON
• Visualization Packages (Matplotlib)
• Components Of A Plot, Sub-Plots
• Basic Plots: Line, Bar, Pie, Scatter
• Advanced Python Data Visualizations
MODULE 5: STATISTICS
• Descriptive And Inferential statistics
• Types Of Data, Sampling types
• Measures of Central Tendencies
• Data Variability: Standard Deviation
• Z-Score, Outliers, Normal Distribution
• Central Limit Theorem
• Histogram, Normality Tests
• Skewness & Kurtosis
• Understanding Hypothesis Testing
• P-Value Method, Types Of Errors
• T Distribution, One Sample T-Test
• Independent And Relational T Tests
• Direct And Indirect Correlation
• Regression Theory
MODULE 6: MACHINE LEARNING INTRODUCTION
• Machine Learning Introduction
• ML core concepts
• Unsupervised and Supervised Learning
• Clustering with K-Means
• Regression and Classification Models.
• Regression Algorithm: Linear Regression
• ML Model Evaluation
• Classification Algorithm: Logistic Regression
MODULE 1: DATA ANALYSIS FOUNDATION
• Data Analysis Introduction
• Data Preparation for Analysis
• Common Data Problems
• Classification of Analytics
• Various Tools for Data Analysis
MODULE 2: Time Series and Trend Analysis
• Introduction to Time Series Data
• Preparing data for Time Series Analysis
• Types of Trends
• Trend Analysis of the Data with Excel
• Insights from Trend Analysis
• Hands-on Case Study: Trend Analysis
MODULE 3: RANKING ANALYSIS
• Introduction to Ranking Analysis
• Data Preparation for Ranking Analysis
• Performing Ranking Analysis with Excel
• Insights for Ranking Analysis
• Hands-on Case Study: Ranking Analysis
MODULE 4: BREAK-EVEN ANALYSIS
• Concept of Breakeven Analysis
• Make or Buy Decision with Break Even
• Preparing Data for Breakeven Analysis
• Hands-on Case Study: Procurement Decision with break even
MODULE 5: PARETO (80/20 RULE) ANALSYSIS
• Pareto rule Introduction
• Preparation Data for Pareto Analysis
• Insights on Optimizing Operations with Pareto Analysis
• Performing Pareto Analysis on Data
• Hands-on case study: Pareto Analysis
MODULE 6: VARIANCE AND FREQUENCY ANALYSIS
• Concept of Variability and Variance
• Data Preparation for Variance Analysis
• Business use cases for Variance and Frequency Analysis
• Performing Variance and Frequency Analysis
• Hands-on case study 1: Variance Analysis
• Hands-on case study 2: Frequency Analysis
MODULE 7: COMPARISION AND CORRELATION ANALYSIS
• Data comparison Introduction
• Concept of Correlation
• Calculating Correlation with Excel
• Comparison vs Correlation
• Performing Comparison Analysis on Data
• Performing correlation Analysis on Data
• Hands-on case study 1: Comparison Analysis
• Hands-on case study 2 Correlation Analysis
MODULE 8: DATA ANALYSIS BUSINESS REPORTING
• Management Information System Introduction
• Various Data Reporting formats
• Creating Data Analysis reports as per the requirements
• Presenting the reports
• Hands-on case study: Create Data Analysis Reports
MODULE 1: DATA ANALYTICS FOUNDATION
• Business Analytics Overview
• Application of Business Analytics
• Visual Perspective
• Benefits of Business Analytics
• Challenges
• Classification of Business Analytics
• Data Sources
• Data Reliability and Validity
• Business Analytics Model
MODULE 2: OPTIMIZATION MODELS
• Prescriptive Analytics with Low Uncertainty
• Mathematical Modeling and Decision Modeling
• Break Even Analysis
• Product Pricing with Prescriptive Modeling
• Building an Optimization Model
• Case Study 1 : WonderZon Network Optimization
• Assignment 1 : KERC Inc, Optimum Manufacturing Quantity
MODULE 3: PREDICTIVE ANALYTICS WITH REGRESSION
• Mathematics beyond Linear Regression
• Hands on: Regression Modeling in Excel
• Case Study 2 : Sales Promotion Decision with Regression Analysis
• Assignment 2 : Design Marketing Decision board for QuikMark Inc.
MODULE 4: DECISION MODELING
• Prescriptive Analytics with High Uncertainty
• Comparing Decisions in Uncertain Settings
• Decision Trees for Decision Modeling
• Case Study 3 : Decision modeling of Internet Plans, Monte Carlo Simulation
• Case Study 4 : Kickathlon Sports Retailer Supplier Decision Modeling
MODULE 1: BUSINESS INTELLIGENCE INTRODUCTION
• What Is Business Intelligence (BI)?
• What Bi Is The Core Of Business Decisions?
• BI Evolution
• Business Intelligence Vs Business Analytics
• Data Driven Decisions With Bi Tools
• The Crisp-Dm Methodology
MODULE 2: BI WITH TABLEAU: INTRODUCTION
• The Tableau Interface
• Tableau Workbook, Sheets And Dashboards
• Filter Shelf, Rows And Columns
• Dimensions And Measures
• Distributing And Publishing
MODULE 3: TABLEAU: CONNECTING TO DATA SOURCE
• Connecting To Data File , Database Servers
• Managing Fields
• Managing Extracts
• Saving And Publishing Data Sources
• Data Prep With Text And Excel Files
• Join Types With Union
• Cross-Database Joins
• Data Blending
• Connecting To Pdfs
MODULE 4: TABLEAU : BUSINESS INSIGHTS
• Getting Started With Visual Analytics
• Drill Down And Hierarchies
• Sorting & Grouping
• Creating And Working Sets
• Using The Filter Shelf
• Interactive Filters
• Parameters
• The Formatting Pane
• Trend Lines & Reference Lines
• Forecasting
• Clustering
MODULE 5: DASHBOARDS, STORIES AND PAGES
• Dashboards And Stories Introduction
• Building A Dashboard
• Dashboard Objects
• Dashboard Formatting
• Dashboard Interactivity Using Actions
• Story Points
• Animation With Pages
MODULE 6: BI WITH POWER-BI
• Power BI basics
• Basics Visualizations
• Business Insights with Power BI
The term data analytics refers to the process of scrutinizing datasets to derive conclusions about the information they contain. Data analytic techniques enable you to take raw data and discover patterns to extract valuable insights from it.
Anyone who wants to learn more about data science and analytics is welcome to enrol in the course. A Bachelor's degree with at least 50% overall or an equivalent grade from a reputable university, ideally in the fields of science or computer science, is the minimal requirement for admission to a postgraduate Data Analytics study.
The fee would differ from institute to institute and the level of training you are looking for. The Data Analytics training fee ranges from 403 USD to 1286.31 USD.
It can take anywhere from 6 weeks to two years to develop the abilities needed to be successful in data analytics. 4 months of training can be an excellent way to become well-versed in data analytics and be adept in it. The fact that there are many distinct paths to a career in data analytics explains the wide range.
Every industry needs data analysts, and they have a variety of job designations. Typical sectors include retail, healthcare, banking and finance, transportation, education, construction, and technology. You can be a Data Analytics, Data scientist, Business Intelligence Analyst, Data Engineer, Quantitative Analyst, Data Analytics Consultant, Operations Analyst, Marketing Analyst, Project Manager, IT Systems Analyst, and Transportation Logistics Specialist to name a few.
It would be beneficial to learn data analytics if you had technical abilities like data analysis, statistical knowledge, data narrative, communication, and problem-solving. Data analysts who frequently collaborate with business stakeholders are said to benefit from having strong business intuition and strategic thinking.
DataMites is the best institute for you if you are willing to make a career out of the analytics domain. The course curriculum is aptly sketched out and the lead mentors are industry-oriented with expert knowledge. We offer hands-on practice with projects and internship opportunities!
There are no prerequisites as such for DataMites Data Analytics Training as the syllabus is sketched out to train candidates from level 1, however, having prior knowledge of programming language, databases, data structures, mathematics and algorithms will only be an added advantage.
The greatest credential in data analytics is the Certified Data Analyst course, which certifies your ability to confidently assess data using a number of technologies. Certification demonstrates your proficiency in handling data, conducting exploratory research, comprehending the fundamentals of analytics, and visualizing, presenting, and elaborating on your findings. The DataMites CDA Course is recognized by IABAC, and the prestigious Jain University.
DataMites data analyst certification training is your best bet in the domain. Our data analytics training gives you concrete evidence that you are qualified to assist businesses, even well-known multinationals, in deciphering the meaning of the data at hand. In contrast to a data analytics certificate, it is proof that you are qualified to perform the duties of a certain job role in accordance with industry standards.
The DataMites Data Analytics Training is meticulously designed and organised in accordance with the fact that the entire domain is expertly explained to newcomers to the field. With that said, you can enlist without a second thought if learning analytics interests you.
DataMites™ is the global institute for Data Science accredited by the International Association of Business Analytics Certifications (IABAC).
At DataMites the fee for Data Analytics Training will be approximately 538 USD in the US, 501.84 Euro in the European Countries and 42,000 INR in India.
At DataMites you will have data analytics training for 4 months.
If you're interested in a career as a data analyst, you should definitely complete the DataMites Certified Data Analyst Training. Our programme guarantees to provide the information, assurance, and credentials required to launch a data analyst profession from scratch.
The IABAC and JainX international recognised authorities, whose credentials you would acquire following the course completion, have accredited the Certified Data Analyst curriculum, one of the best data analytics programmes provided by DataMites. The DataMites Certified Data Analyst credential is the best approach to launch a career in data analytics.
DataMites offers flexible learning methods for candidates, ranging from online data analyst training to highly interactive classroom training in data analytics. The choice is all yours.
We are adamant about providing you with instructors who are certified and highly qualified with decades of experience in the industry and well versed in the subject matter.
Our Flexi-Pass for Data Analytics Training grants candidates to attend sessions from Datamites for a period of 3 months related to any query or revision you wish to clear.
We will issue you with IABAC® certification that would provide global recognition of the relevant skills.
Indeed, DataMites Data Analytics Training does come with the course completion certificate which will be handed to you after completion of the course.
You don't have to stress about it. To arrange a class that fits your schedule, simply contact your trainers. For online training, each session will be recorded and uploaded so you can simply catch up on anything you skipped at your own speed and comfort.
You can make payments to us through Cash, Credit Card, PayPal, Visa, Master Card, American Express, Net Banking, Cheque and Debit Card!
The DataMites Placement Assistance Team(PAT) facilitates the aspirants in taking all the necessary steps in starting their career in Data Science. Some of the services provided by PAT are: -
The DataMites Placement Assistance Team(PAT) conducts sessions on career mentoring for the aspirants with a view of helping them realize the purpose they have to serve when they step into the corporate world. The students are guided by industry experts about the various possibilities in the Data Science career, this will help the aspirants to draw a clear picture of the career options available. Also, they will be made knowledgeable about the various obstacles they are likely to face as a fresher in the field, and how they can tackle.
No, PAT does not promise a job, but it helps the aspirants to build the required potential needed in landing a career. The aspirants can capitalize on the acquired skills, in the long run, to a successful career in Data Science.
