Data Analytics Online Course in Pune

Job Oriented Training

Welcome to the Data Analysis Courses in Pune, your gateway to unlocking the world of possibilities through data insights. At 3RI Technologies, we believe in transforming your data skills into a powerful asset for the future. Are you ready to embark on a learning journey that not only equips you with the latest in data analytics but also propels your career to new heights?

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Key Features

Course Duration : 5 Months

Live Projects : 4

Online Live Training

EMI Option Available

Certification & Job Assistance

24 x 7 Lifetime Support

Our Industry Expert Trainer

We are a team of 10+ Years of Industry Experienced Trainers, who conduct the training with real-time scenarios.
The Global Certified Trainers are Excellent in knowledge and highly professionals.
The Trainers follow the Project-Based Learning Method in the Interactive sessions.

Data Analytics Course in Pune

Overview
In the rapidly evolving digital landscape, the requirement of talented and professional data analysts is highly critical. Our Data Analytics Course in Pune is preciously planned to fill the crack between the bookish-part and real-life applications. So, it does not matter whether you are new comer or newbie to technology world or you are pro, our course provides a wide-ranging learning experience tailored to boost your analytical proficiency.
Why choose Data Analytics as a Career?

Selecting a job in data analytics is akin to entering a market where your abilities are greatly valued in a variety of industries. Data Analyst career is really a versatile career option that provides you work in a broad domain such as finance, healthcare, marketing, and more. Its scope is unlimited.

As a data analyst, you get to solve important problems, make impactful decisions, and contribute to the success of businesses. In addition to this the field of data analysis is expanding quickly, providing many of chances for career growth and high salaries.

Learning never stops in data analytics, and your skills are globally relevant, opening doors to work on exciting projects around the world. It’s not just a job; it’s a journey of continuous learning, problem-solving, and making a real difference.

In a nutshell, choosing a career in Data Analytics means joining a dynamic field where your skills are valued, and you have the chance to make a positive impact. It’s about having a versatile and exciting career that offers growth, learning, and the satisfaction of contributing to meaningful outcomes in the business world.

Prerequisites for Data Analytics Course in Pune

Embarking on the journey of data analytics requires passion and a basic understanding of mathematics. Our educational program is readily available and beneficial for both amateurs and experienced experts aiming to broaden their intellectual ideas since it is customized to individuals with a variety of experience.

What is the total duration of the training programme?

Flexibility is key to effective learning. Our Data Analytics Course in Pune proffers a wide-ranging curriculum that fits into your schedule. With a duration of [Specify Duration], we attempt to ensure you get an in-depth education without conflicting with your regular obligations.

Learning Data Analytics in Pune with 3RI Technologies

Choosing 3RI Technologies means choosing excellence in education. Our collective of experienced instructors provides a plethora of industry knowledge to the classroom, creating an environment where learning goes beyond textbooks. We make sure you are knowledgeable about the most recent tools and methods in data analytics with a curriculum designed in conjunction with industry professionals.

What is Data Analytics?

Data analytics is the art and science of interpreting complex datasets to uncover valuable insights, trends, and patterns. Finding important trends, patterns, and insights in large, complicated datasets through interpretation is the art and science of data analytics.

We explore the nuances of data analytics in this course, giving you the tools to solve business problems, spur creativity, and make wise decisions. From deciphering market trends to predicting consumer behavior, the applications of Data analytics has many broad and revolutionary.

Difference between Data Analysts and Data Scientists

Both the profiles: Data analysts and Data scientists play with Data, but these two profiles are loaded with distinctive roles and accountabilities. Here’s a major difference between these two Profile:

Data Analyst:

  • Focus:The primary objective of interpreting and analyzing data for data analysts is help businesses in making legitimate business decisions.
  • Skills: They are skilled in data cleansing, statistical analysis, and visualization methods. Excel, SQL, and business intelligence tools are commonly used.
  • Tasks: Data analysts process and analyze historical data, create reports, and generate insights to answer specific business questions.
  • Objective: The objective is to help with decision-making through presenting an in-depth knowledge of both historical and modern patterns.

Data Scientist:

  • Focus: A data scientist’s primary focus is on developing new algorithms and data analysis procedures for data modeling and production.
  • Skills: They have advanced skills in programming (Python, R), machine learning, and statistical modeling. Data scientists frequently function with massive data technologies and are capable of handling unstructured data.
  • Tasks: Data scientists work on predictive and prescriptive analysis, build machine learning models, and develop algorithms to uncover patterns and trends for future decision-making.
  • Objective: The goal is to extract actionable insights, build models, and make predictions for future trends or outcomes.

Searching for a Data Scientist course in Pune? We are here for you. 3RI Technologies offering a complete Data Analyst course in Pune

What will you get after certification?

The rewards of completing our Data Analytics Course in Pune extend beyond knowledge. With globally recognized certifications, you not only validate your expertise but also gain a competitive edge in the job market. From enhanced career prospects to the ability to contribute meaningfully to organizational success, the benefits are limitless.

Data Analytics employment opportunities

Pune, a thriving hub of technology and innovation, presents a myriad of opportunities for skilled data analysts. By enrolling in our course, you position yourself for a rewarding career in fields such as data analysis, business intelligence, and decision science. The range of possible careers matches the variety of data sets you will examine.

What role does Data Analytics play?

Data Analytics plays a pivotal role in various areas:

  • Informed Decision-Making: empowers data-driven assessment-making for better outcomes.
  • Business Intelligence: Provides insights into markets, customers, and industry trends.
  • Operational Efficiency: Identifies inefficiencies and optimizes processes.
  • Customer Insights: Understands customer behavior for personalized experiences.
  • Risk Management: Finds and reduces potential risks.
  • Healthcare: Improves patient care, treatment, and medical research.
  • Fraud Detection: Detects and prevents fraud in various industries.
  • Supply Chain Optimization: Optimizes inventory, forecasting, and logistics.
  • Environmental Monitoring: Monitors environmental changes and assesses human impact.

Skills Required

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Data Analytics Course Syllabus

Decade Years Legacy of Excellence | Multiple Cities | Manifold Campuses | Global Career Offers

1. Fundamentals of Data Science and Mathematical statistics
    ● Introduction to Data Science
    ● Need of Data Science
    ● BigData and Data Science
    ● Data Science and machine learning
    ● Data Science Life Cycle
    ● Data Science Platform
    ● Data Science Use Cases
    ● Skill Required for Data Science
2. Mathematics For Data Science
    ● Linear Algebra-Matrices
        o Zero
        o One
        o Identify
        o Diagonal
        o Column
        o Row
        o Operations
3. Introduction to Statistics
    ● Descriptive vs. Inferential Statistics
    ● Types of data
    ● Measures of central tendency and dispersion
    ● Hypothesis & inferences
    ● Hypothesis Testing
    ● Confidence Interval
    ● Central Limit Theorem
4. Probability and Probability Distributions
    ● Probability Theory
    ● Conditional Probability
    ● Data Distribution
    ● Distribution Functions
        o Normal Distribution
        o Binomial Distribution

1. Using a Spreadsheet
    ● What is Excel?
    ● Why Use Excel?
    ● Excel Overview
    ● Excel Ranges, Selection of Ranges
    ● Excel Fill, Fill Copies, Fill Sequences,Sequence of Dates
    ● Excel adds, move, and delete cells
    ● Excel Formulas
    ● Relative and Absolute References
2. Functions
    ● SUM
    ● AVERAGE
    ● COUNT
    ● MAX & MIN
    ● RANDBETWEEN
    ● TRIM
    ● LEN
    ● CONCATENATE
    ● TODAY & NOW
3. Advanced Functions
    ● Excel IF Function
    ● Excel If Function with Calculations
    ● How to use COUNT, COUNTIF, and
    ● COUNTIFS Function?
4. Data Visualization
    ● Excel Data Analysis – Data Visualization
    ● Visualizing Data with Charts
    ● Chart Elements and Chart Styles
    ● Data Labels
    ● Quick Layout

    ● An Introduction to RDBMS & SQL
    ● Data Retrieval with SQL
    ● Pattern matching with wildcards
    ● Basics of sorting
    ● Order by clause
    ● Aggregate functions
    ● Group by clause
    ● Having clause
    ● Nested queries
    ● Inner join
    ● Multi join
    ● Outer join
    ● Adding and Deleting columns
    ● Changing column name and Data Type
    ● Creating Table from existing Table
    ● Changing Constraints Foreign key

1. An Introduction to Python

    ● Why Python , its Unique Feature and where to use it?
    ● Python environment Setup/shell
    ● Installing Anaconda
    ● Understanding the Jupyter notebook
    ● Python Identifiers, Keywords
    ● Discussion about installed module s and packages
2. Conditional Statement ,Loops and File Handling
    ● Python Data Types and Variable
    ● Condition and Loops in Python
    ● Decorators
    ● Python Modules & Packages
    ● Python Files and Directories manipulations
    ● Use various files and directory functions for OS operations
3. Python Core Objects and Functions
    ● Built in modules (Library Functions)
    ● Numeric and Math’s Module
    ● String/List/Dictionaries/Tuple
    ● Complex Data structures in Python
    ● Python built in function
    ● Python user defined functions
4. Introduction to NumPy
    ● Array Operations
    ● Arrays Functions
    ● Array Mathematics
        ▪ Mean
        ▪ Standard Deviation
        ▪ Max
        ▪ Min
    ● Array Manipulation
        ▪ Reshaping
        ▪ Resizing
    ● Array I/O
    ● Matrix creation
    ● Data generation
    ● Random function
    ● Normalized Data Generation
    ● Indexing and Slicing
    ● Transpose
    ● Importing Files with Numpy
5. Data Manipulation with Pandas
    ● Data Frames
    ● Series
    ● I/O
    ● Creating Pandas DataFrame
    ● Selection in DFs
    ● Data Describe
    ● Data info
    ● Retrieving in DFs
    ● Applying Functions
    ● Reshaping the DFs – Pivot
    ● Combining DFs Merge Join
    ● Data Alignment
6. SciPy
    ● Hypothesis Testing using Scipy
    ● Shapiro Test
    ● Spearmaman Test
    ● T-Test of Independents
    ● Chi-Square Test
7. Visualization with Seaborn
    ● Seaborn Installation
    ● Introduction to Seaborn
    ● Basics of Plotting
    ● Plots Generation
    ● Visualizing the Distribution of a Dataset
    ● Selection color palettes
8. Visualization with Matplotlib
    ● Matplotlib Installation
    ● Matplotlib Basic Plots & it’ s Containers
    ● Matplotlib components and properties
    ● Scatter plots
    ● 2D Plots
    ● Histograms
    ● Bar Graphs
    ● Pie Charts
    ● Box Plots
    ● Customization
    ● Store Plots
9. Descriptive Statistics
    ● Data understanding
    ● Observations, variables, and data matrices
    ● Types of variables
    ● Measures of Central Tendency
    ● Arithmetic Mean / Average
        ▪ Merits & Demerits of Arithmetic Mean and Mode
        ▪ Merits & Demerits of Mode and Median
        ▪ Merits & Demerits of Median Variance
10. Probability Basics
    ● Notation and Terminology
    ● Unions and Intersections
    ● Conditional Probability and Independence
11. Probability Distributions
    ● Random Variable
    ● Parameters vs. Statistics
    ● Binomial Distribution
    ● Central Limit Theorem
12. Tests of Hypothesis
    ● Large Sample Test
    ● Small Sample Test
    ● One Sample: Testing Population Mean
    ● Hypothesis in One Sample z-test
    ● Two Sample: Testing Population Mean
    ● One Sample t-test – Two Sample t-test
    ● Paired t-test
    ● Hypothesis in Paired Samples t-test
    ● Chi-Square test
13. Data Analysis
    ● Case study- Netflix
    ● Deep analysis on Netflix data

1. Exploratory Data Analysis
    ● Data Exploration
    ● Missing Value handling
    ● Outliers Handling
    ● Feature Engineering
    ● Train-Test Split
    ● Standard Scaler
    ● Min-Max Scaler
    ● Data Preprocessing
    ● Resampling
        ▪ Up-Sampling
        ▪ Down-Sampling
2. Machine Learning: Supervised Algorithms Classification
    ● Introduction to Machine Learning
    ● Linear Regression
    ● Multiple Linear Regression
    ● Gradient Descent
    ● Logistic Regression
        ▪ Binary Classification
        ▪ Multiclass classification
    ● Naïve Bays Algorithm
    ● K-Nearest Neighbor Algorithm
    ● Decision Tress
        1. Classification
        2. Regression
    ● Support Vector Machines
    ● Random Forest
    ● Model Evaluation and performance
        ▪ Accuracy ,Precision
        ▪ Recall
        ▪ F1 Score
        ▪ Confusion Matrix
        ▪ Classification Report
        ▪ K-Fold Cross Validation
        ▪ ROC, AUC etc…
    ● Hyper parameter tuning
3. Machine Learning: Unsupervised Learning Algorithms
    ● Similarity Measures
    ● Cluster Analysis and Similarity Measures
    ● K-Means Clustering
        ▪ Elbow Method
    ● Hierarchical Clustering
        ▪ Agglomerative Clustering
    ● K-Nearest Neighbors
4. Ensemble algorithms
    ● Bagging
        ▪ Random Forest
    ● Boosting
        ▪ Adaboost
    ● Voting
    ● Stacking
    ● Principal Components Analysis
5. Recommendation Systems
    ● Collaborative filtering model
    ● Content-based filtering model.
    ● Hybrid collaborative system

1. Artificial Intelligence
    ● An Introduction to Artificial Intelligence
    ● History of Artificial Intelligence
    ● Future and Market Trends in AI
    ● Intelligent Agents – Perceive-ReasonAct Loop
    ● Constraint-based Reasoning
2. Deep networks and structured knowledge
    ● Studying Neural Elements
    ● Neural Networks and Perceptions
    ● Understanding Feedforward Networks
    ● Exploring Backpropagation
    ● Working of Neural Networks
3. Natural Language Processing
    ● Natural Language Processing
    ● NLP in Python
    ● Tokenization
    ● Part of Speech Tagging (POS Tagging)
    ● Named Entity Recognition
    ● Semantic Analysis
    ● Sentiment Analysis
4. Artificial Neural Network
    ● Understanding Artificial Neural Network
    ● The Activation Function
    ● Building an ANN
    ● Building Problem Description
    ● Evaluation the ANN
    ● Improving the ANN
    ● Tuning the ANN.
5. Conventional Neural Networks
    ● CNN Intuition
    ● Convolution Operation
    ● Kernel Operation
    ● Filtering operation
    ● Padding on image
    ● Pooling Layer
    ▪ Max Pooling
    ▪ Average Pooling
    ● ReLU Layer
    ● Fully Connected Dense Layer
    ● Softmax and Cross-Entropy
    ● Building a CNN
    ● Evaluating the CNN
    ● Improving the CNN
    ● Tuning the CNN
6. Recurrent Neural Network
    ● Recurrent Neural Network
    ● RNN Intuition
    ● The Vanishing Gradient Problem
    ● LSTMs and LSTM Variations
    ● Practical Intuition
    ● Building an RNN
    ● Evaluating the RNN
    ● Improving the RNN
    ● Tuning the RNN
7. Time Series Data
    ● Introduction to Time series data
    ● Data cleaning in time series
    ● Pre-Processing Time-series Data
    ● Prediction in Time Series using LSTM
    ● Prediction in Time Series using ARIMA

1. Introduction to Git & Distributed Version Control
2. Life Cycle
3. Create clone & commit Operations
4. Push & Update Operations
5. Stash, Move, Rename & Delete Operations.

1. Machine Learning Features & Services
    ● Using python in Cloud
    ● Understanding Google Colab
    ● Understanding Jupyter Lab
    ● How to access Machine Learning Services
    ● Lab on accessing Machine learning services
    ● Uploading Data
    ● Preparation of Data
    ● Applying Machine Learning Model

1. Introduction to Data Visualization & Power of Tableau
    ● Architecture of Tableau
    ● Product Components
    ● Working with Metadata and Data Blending
    ● Data Connectors
    ● Data Model
    ● File Types
    ● Data Source Filters
2. Scatter Plot
    ● Funnel Chart
    ● Waterfall Chart
    ● Working with Filters
    ● Organizing Data and Visual Analytics
    ● Working with Mapping
    ● Working with Calculations and Expressions
    ● Working with Parameters
    ● Charts and Graphs
    ● Dashboards and Stories
Data Visualization with PowerBI
3. Introduction to Data Visualization & Power of Tableau
    ● Architecture of Tableau
    ● Product Components
    ● Working with Metadata and Data Blending
    ● Data Connectors
    ● Data Model
    ● File Types
    ● Data Source Filters
4. Scatter Plot
    ● Funnel Chart
    ● Waterfall Chart
    ● Working with Filters
    ● Organizing Data and Visual Analytics
    ● Working with Mapping
    ● Working with Calculations and Expressions
    ● Working with Parameters
    ● Charts and Graphs

Project Work and Case Studies
    ❖ Machine Learning end to end Project blueprint
    ❖ Case study on real data after each model.
    ❖ Regression predictive modeling – E-commerce
    ❖ Classification predictive modeling – Binary Classification
    ❖ Case study on Binary Classification – Bank Marketing
    ❖ Case study on Sales Forecasting and market analysis
    ❖ Widespread coverage for each Topic
    ❖ Various Approaches to Solve Data Science Problem
    ❖ Pros and Cons of Various Algorithms and approaches
    ❖ Amazon-Recommender
    ❖ Image Classification Sentiment Analysis
Project Domain: FINANCE
    ● The insurance company wants to decide on the premium using various parameters of the client.
    ● It’ s an important problem to keep the clients and attract new ones.
By completing this Project you will learn:
    ● How to collect data?, how to justify the right features? , Which ML / DL model is best in this situation? How much data is enough?
    ● How to have CI/CD in the project?
    ● How to do Deployment of Project to cloud?
Project Domain: Image Processing in Health care
    ● A hospital wants to automate the Detection of pneumonia in X-rays using image processing.
By completing this Project you will learn:
    ● How to handle image data? How to preprocess and augment image data?
    ● How to choose the right model for the image process?
   ● How to apply transfer learning in image processing?
    ● How to do incremental learning & CI/CD in the project?
    ● How to do Deployment of Project to cloud?

Natural Language Processing
    ● One of the companies wants to automate applicant’ s level in English communication.
    ● Create a ML/DL model for this task.
By completing this Project you will learn:
    ● How do convert text to the right representation?
    ● How to preprocess text data? How to select the right ML/DL model for text data?
    ● How to do transfer learning in Text Analytics?
    ● How to do CI/CD in a text analytics project? How to do Deployment of Project to cloud?
Mechanical
    ● A mechanical company wants to perform predictive maintenance of engine parts.
    ● This enables the company to efficiently change parts before the machine fails.
By completing this Project you will learn:
    ● How to handle time-series data?
    ● How to preprocess time series data?
    ● How to create ML/DL model for Time-series Data?
    ● How to do CI/CD in a text analytics project?
    ● How to do Deployment of Project to cloud?
Sales / Demand Forecasting
    ● Predict the sales/demand of a product of a company.
    ● Sales / Demand forecasting of the product will help the company efficiently manage the resources.
    ● Create a ML/DL model for this problem.
By completing this Project you will learn:
    ● How to handle time-series data?
    ● How to preprocess time series data?
    ● How to create ML/DL model for Time-series Data?
    ● How to do CI/CD in a text analytics project? How to do Deployment of Project to cloud?

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Schedule Your Batch at your convenient time.

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Will I Get Certified?

Upon successfully completing this program, you’ll earn a certificate.

The 3RI certification is accepted and respected by every significant multinational company across the nation. Fresh graduates and corporate trainees are eligible for the assistance. We offer certificate once the academic and practical courses have been finished. The certification that we offer here at 3RI is recognized across the country. The value of your resume will grow as a result. With the assistance of this qualification, you will be able to obtain prominent employment posts in the most successful multinational corporations in the country. The completion of our course as well as the projects that are based on practical application, are prerequisites for receiving the certificate.

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Data Analytics Online Course Certification

Who can get this Data Analytics course and Training?

This Data Analytics course is suitable for:

  1. Beginners:

Perfect for those new to data analytics, starting from basics for a smooth learning journey.

  1. Working Professionals:

Designed for experts willing to advance their careers or transition into positions through data.

  1. Business and Marketing Pros:

Valuable for professionals wanting to use data for strategic decision-making and business insights.

  1. IT and Tech Professionals:

Beneficial for IT professionals looking to specialize in data analytics and use cutting-edge technologies.

  1. Students and Graduates:

Ideal for students and recent graduates, providing practical knowledge and standout certifications.

  1. Aspiring Data Scientists:

A foundational course for those aspiring to become data scientists, covering key concepts and tools.

  1. Curious Individuals:

Welcoming anyone curious about data, with only basic math knowledge and a passion for exploration needed.

  1. Career Transition Seekers:

Support for those who are considering a transition into the attractive subject of data analytics as a career.

Data Analytics Classes in Pune: Learn with 3RI Technologies

Our Data Analytics Classes in Pune are designed to provide a 360 degree learning experience. Dive into hands-on sessions, group discussions, and real-world case studies, ensuring that you gain practical expertise in alongside your knowledge of concepts set you apart in the competitive job market.

Data Analytics Course in Pune Certifications

Boost your career prospects with relevant certifications:

  1. Microsoft Certified: Data Analyst Associate
  • Microsoft’s stamp of approval for your data analytics proficiency.
  1. Google Data Analytics Professional Certificate
  • A testament to your skills recognized by one of the tech giants.
  1. IBM Data Science Professional Certificate
  • Unleash the power of data science with this prestigious certification.
  1. Cloudera Certified Associate (CCA) Data Analyst
  • Validate your skills in handling big data with Cloudera’s industry-recognized certification.
  1. SAS Certified Data Scientist
  • Master the world of analytics with this globally acknowledged certification.
  1. Tableau Desktop Specialist
  • Showcase your expertise in data visualization with Tableau’s specialized certification.
  1. Data Analyst Nanodegree
  • Propel your career forward with this comprehensive nanodegree program.
  1. Certified Analytics Professional (CAP)
  • Become a certified analytics professional, recognized for your competence in the field.
  1. DASCA Data Science Certifications
  • A suite of certifications to validate your data science skills across various domains.
  1. MicroMasters Program in Data Science
  • A comprehensive program offering a deep dive into the foundations of data science.

 

Frequently Asked Questions
What is Data Analytics?

In the multifaceted field of data analytics, raw data is analyzed, investigated, and converted into valuable information. It includes a range of approaches, statistical procedures, and instruments to find patterns, trends, and important data that can guide strategic decision-making.

Who can benefit from a Data Analytics course?

Our Data Analytics Course is designed to cater to a diverse audience. Whether you’re a newcomer to the field, a business professional looking to enhance analytical skills, or an IT professional seeking to specialize in data analysis, this course provides a comprehensive learning experience for individuals at all career stages.

How long is the duration of the Data Analytics course?

The duration of this Data Analytics Course programme is [Specify Duration]. This timeframe is carefully designed to strike a balance between depth of learning and flexibility, allowing participants to grasp the intricacies of data analytics without compromising other commitments.

What software or tools will I learn during the course?

You will obtain practical experience working with prominent industry tools such as [Specify Tools]. These tools are widely used in the data analytics field, ensuring that you acquire practical skills and are well-prepared for real-world applications.

Are there any necessities for enrolling in the course?

Despite having an elementary knowledge of mathematics is beneficial, there are not any rigorous requirements for enrolling in the Data Analytics Course. The course has been developed with inclusivity and accessibility in mind, with adjustments meant to suit students from diverse backgrounds.

Will I be earning a certificate upon completion of the course?

Yes, post the successful completion of the Data Analytics Course, you will earn certifications from both 3RI Technologies and the associated institutions. These certifications will boost your worth in the job market and function as evidence of your obtained skill.

Is there any job assistance or placement support provided after completing the course?

Absolutely! Our dedicated placement support team is committed to assisting you in exploring job opportunities, refining your resume, and preparing for interviews. Our goal is to make sure you have an easy transition into the workforce and are set up for success.

List of skills covered in this Data Analytics Training?

In this Data Analyst Course, you will be able to ace below shared skills :

  • SQL
  • Python
  • Statistics And Probability
  • Machine Learning
  • Performance Metrics
  • Time Series Forecasting
  • Data Modeling
  • PowerBI
  • Microsoft Excel
Why is Data Analytics important in today's world?

In the contemporary world, where data is generated at an unprecedented rate,  data analytics is essential in order to get useful insights. Organizations leverage data analytics to make informed decisions, identify market trends, enhance operational efficiency, and gain an advantage against competitors in their respective fields.

What topics are covered in the Data Analytics course?

The curriculum includes a wide range of themes to ensure a well-rounded understanding of data analytics. Key areas include data exploration, statistical analysis, machine learning algorithms, data visualization techniques, and practical applications of analytics in various industries.

Is this Data Analytics course best fit for beginners with zero experience?

Absolutely! Our course is crafted to accommodate individuals who have various backgrounds, comprising novices with scant or no background in data analytics. The curriculum is designed to give participants a solid basis for learning through the addition of advanced subjects progressively after covering foundational ones.

Can I take the course online from Pune?

Yes, our online platform provides the flexibility for participants in Pune to access the Data Analytics Course remotely. This online format allows you to learn at your own pace, providing convenience without compromising the quality of education.

What is the teaching methodology for the online Data Analytics course?

The online Data Analytics Course employs a dynamic teaching methodology that includes live sessions, recorded videos, and interactive assignments. This approach ensures an engaging learning experience, fostering both theoretical understanding and practical application of data analytics concepts.

How can I pay for the Data Analytics course?

We empower the participants with numerous payment alternatives, such as [Specify Payment alternatives] in order to satisfy different financial preferences. Our goal is to make the Data Analytics Course accessible to individuals committed to enhancing their skills and advancing their careers.

Will I be able to access all the course materials and lectures after the course is completed in future?

Yes, you will be able to access the complete course materials and lectures after the course is completed in future. With the assistance of this function, you can review and strengthen your knowledge whenever essential, even after completing the course. It is an important tool for continuous learning and reference during your entire professional life.

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Data Analytics Information


Data Analytics Certification Training locations in Pune:
 Pune City, Aundh (411007), Gokhalenagar (411016), Kothrud (411029), Baner (411004), Shivajinagar (411005), Parvati (411009), Kondhwa (411048), Navsahyadri (411052), Chatursringi (411053), Pimpri Chinchwad (411078), Pimple Gurav (411061), Pimple Nilakh (411027), Pimple Saudagar (411027), Pimple Khed (411017), Pimple Jagtap (411061), Rahatani (411017), Wakad (411057), Balewadi (411045), Vishal Nagar (411027), Thergaon (411033), Shivaji Nagar (Pimpri-Chinchwad) (411017), Sangvi (411027), Jagtap Dairy (411027)

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