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Data Analytics Training in HSR Layout

22369 Ratings

Rated #1 Recognized as the No.1 Institute for Data Analytics Training in HSR Layout

Our Data Analytics Training in HSR Layout Offers a Detailed, Hands-On Learning Experience Designed to Help You Master Essential Data Analytics Skills, Including Data Analysis and Business Intelligence Techniques.

Important Subjects Covered in the Course Include Statistical Analysis, Data Preparation, Data Visualization, Analytical Methods, and Predictive Modelling. With Hands-On Experience Using Industry-Leading Tools and Methodologies, You Will Be Ready to Tackle Real-World Data Challenges With Confidence.

  • 24/7 Student Portal Access for Continuous Learning.
  • In-Depth Training with a Blend of Theory and Practice.
  • Specialized Sessions for MNC Interviews & Resume Prep.
  • Advanced Tools and Case Study Training in HSR Layout.
  • Over 12,400 Students Certified | 350+ Job Collaborations.
  • Limited Seats – New Batch Starts Soon for Data Analytics Training in HSR Layout!

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Fee INR 18000

INR 14000

Training

Enroll Now View Syllabus

  • Case Studies and Projects 8+

  • Hours of Training 45+

  • Placement Assurance 100%

  • Expert Support 24/7

  • Support & Access Lifetime

  • Certification Yes

  • Skill Level All

  • Language All

Boost Your Career with Our Data Analytics Training

  • Our Data Analytics Training in HSR Layout is designed for aspiring data professionals who want hands-on, role-specific training aligned with industry needs.
  • This Data Analytics Training emphasizes real-time data processing, automation in Excel/Power BI, Google Analytics, CRM analytics, and KPI dashboards across verticals.
  • Data Analytics Training offers learning modes such as live capstone workshops, self-paced analytics labs, peer discussion forums, and expert-led virtual sessions.
  • Trainers bring deep experience from product companies, helping you master real tools like Python, SQL, Tableau, Power BI, and Google Looker Studio.
  • On completion, learners are ready for positions like Business Analyst, Marketing Analyst, or Dashboard Specialist in data-first companies.
  • Data Analytics Training provides holistic career support including personalized career coaching, mock HR + technical interviews, and job application tracking assistance.
  • You will exit the course not just with skills but with confidence to manage data analytics projects end-to-end and drive measurable business impact.
  • Classroom Batch Training
  • One To One Training
  • Online Training
  • Customized Training
  • Enroll Now

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+91-7669 100 251
Other Categories Placements
  • Non-IT to IT (Career Transition) 2371+
  • Diploma Candidates3001+
  • Non-Engineering Students (Arts & Science)3419+
  • Engineering Students3571+
  • CTC Greater than 5 LPA4542+
  • Academic Percentage Less than 60%5583+
  • Career Break / Gap Students2588+
Top Placement Record

Upcoming Batches

07-July-2025
Weekdays

Weekdays Regular

08:00 AM & 10:00 AM

(Class 1Hr - 1:30Hrs) / Per Session

09-July-2025
Weekdays

Weekdays Regular

08:00 AM & 10:00 AM

(Class 1Hr - 1:30Hrs) / Per Session

12-July-2025
Weekends

Weekend Regular

(10:00 AM - 01:30 PM)

(Class 3hr - 3:30Hrs) / Per Session

13-July-2025
Weekends

Weekend Fasttrack

(09:00 AM - 02:00 PM)

(Class 4:30Hr - 5:00Hrs) / Per Session

    Hear it from our Graduate

    Tools Covered In Data Analytics Course in HSR Layout

    Course Objectives

    Enrolling in a Data Analytics training program equips you with the ability to interpret complex data, make informed decisions, and drive business growth. It opens career opportunities in a fast-growing field where data-driven insights are highly valued. The program also helps you develop technical and analytical skills that are transferable across industries.
    • Basic understanding of math and statistics is helpful but not always required.
    • Familiarity with computers and software use is essential.
    • Some courses recommend knowledge of Excel or similar spreadsheet tools.
    • No prior programming experience is needed for beginner courses.
    • A willingness to learn and analyze data logically is key.
    Data Analytics training typically includes a mix of lectures, hands-on exercises, case studies, and real-world projects. Participants often work with data sets using tools like Excel, SQL, Python, or R to analyze and visualize data. Interactive quizzes and group discussions reinforce key concepts and foster collaborative problem-solving. This blended approach ensures practical understanding alongside theoretical knowledge.
    • Working with real-world datasets to practice data cleaning and transformation.
    • Using tools like Excel, SQL, Python, or R for data analysis and querying.
    • Creating visualizations with tools like Tableau or Power BI.
    • Completing case studies simulating business problems and decision-making.
    • Data collection, cleaning, and preprocessing techniques.
    • Exploratory data analysis and visualization methods.
    • Basics of statistics and probability applied to data.
    • Introduction to SQL, Python/R programming for data tasks.
    • Data storytelling, reporting, and presentation skills.
    Essential skills include strong analytical thinking, problem-solving, and attention to detail to interpret data accurately. Familiarity with statistical concepts and proficiency in tools like Excel, SQL, or programming languages such as Python or R are important. Communication skills are also crucial for presenting findings clearly to non-technical audiences. Curiosity and a willingness to continuously learn new technologies enhance success in the course.
    Yes, many Data Analytics courses are designed for beginners with no prior experience, starting with foundational concepts and gradually advancing to more complex topics. They often provide step-by-step guidance and plenty of practical exercises to build confidence. The curriculum usually covers essential tools and techniques from the ground up, making it accessible for learners new to the field.

    What tools and technologies are used in Data Analytics training?

    • Spreadsheet tools like Microsoft Excel or Google Sheets.
    • SQL databases for querying and managing data.
    • Programming languages such as Python or R for advanced analytics.
    • Visualization tools like Tableau, Power BI, or matplotlib.
    • Cloud platforms and big data tools in advanced courses.

    Is Data Analytics in demand in the job market?

    Data Analytics is highly in demand across various industries including finance, healthcare, retail, and technology. Organizations rely on data insights to improve operations, marketing strategies, and customer experience, fueling a growing need for skilled analysts. Job opportunities continue to expand as businesses invest more in data-driven decision-making.

    What is the future career outlook for Data Analytics professionals?

    • High demand across industries such as finance, healthcare, and retail.
    • Increasing reliance on data for business strategy boosts job growth.
    • Roles include data analyst, business analyst, data scientist, and more.
    • Competitive salaries and opportunities for career advancement.
    • Continuous learning is needed as new tools and techniques evolve.

    Is Data Analytics easy to learn for beginners?

    While Data Analytics involves some technical skills and concepts, many beginners find it manageable with the right training and practice. Courses often break down complex topics into simpler, digestible parts and provide hands-on experience. A logical mindset and curiosity help learners grasp analytical thinking more easily. Like any skill, consistent effort and real-world application are key to mastering Data Analytics over time.
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    Overview of Data Analytics Course in HSR Layout

    Data Analytics is the structured application of statistical and computational techniques to extract actionable insights from raw datasets. The process involves data wrangling, ETL (Extract, Transform, Load) pipelines, descriptive statistics, inferential analysis, machine learning modeling, and data visualization. It relies heavily on programming languages such as Python (pandas, NumPy, matplotlib) and R, along with query languages like SQL and BI tools like Tableau and Power BI. There are four key analytical models: descriptive analytics summarizes past performance; diagnostic analytics explores causality; predictive analytics uses algorithms to forecast future trends; and prescriptive analytics suggests optimal outcomes through decision modeling. In enterprise applications, data analytics is integrated with cloud platforms like AWS and Azure and often interfaces with data lakes and warehouses. Use cases span anomaly detection in fintech, churn analysis in telecom, and cohort tracking in SaaS environments. Professionals aiming to specialize in this domain require proficiency in data structures, linear algebra, statistics, and domain-specific KPIs. In short, data analytics forms the backbone of modern business intelligence and strategic data science operations.

     

    Additional Info

    Roles and Responsibilities of Data Analytics Professionals

    • Data Retrieval: Access and gather data from various sources such as APIs, databases, cloud platforms, and flat files to support analysis efforts.
    • Data Preparation: Clean, organize, and standardize raw data by removing duplicates, correcting errors, and formatting it for efficient analysis.
    • Visualization Design: Create user-friendly dashboards and visual reports using tools like Power BI, Tableau, Excel, or Python to simplify data interpretation.
    • Insight Reporting: Share findings with business leaders in a clear and concise manner to support effective decision-making.
    • Requirement Gathering: Collaborate with stakeholders to understand business goals and translate them into analytical objectives.
    • Trend Forecasting: Build predictive models to estimate future outcomes, customer behaviors, and operational risks based on historical data.
    • Data Integrity & Compliance: Uphold data quality, privacy, and compliance by adhering to data governance standards and best practices.

    Future Scope of Data Analytics Course in HSR Layout

    • Industry-Wide Importance: Data analytics has become a vital tool across sectors such as healthcare, finance, retail, e-commerce, and technology, enabling smarter, insight-driven decisions.
    • Expanding Job Market: As data becomes more central to business strategy, roles like Data Analyst, Data Engineer, BI Developer, and Data Scientist are witnessing strong growth and high demand.
    • Innovative Growth: With rapid advancements in AI, machine learning, big data, and cloud technologies, data analytics is evolving and opening up new possibilities for intelligent decision-making.
    • Career Boost with Certifications: Certifications from top providers like IBM, Google, Microsoft, and SAS add significant value, helping professionals stand out, earn more, and qualify for senior roles.
    • Extensive Toolset Exposure: Professionals work within a robust ecosystem using tools such as Python, SQL, R, Tableau, Power BI, and cloud platforms like AWS, Azure, and GCP.
    • Critical Business Asset: In today’s data-driven environment, analytics plays a central role in improving efficiency, predicting trends, and guiding strategic planning across industries.
    • Gateway to Future Tech: A strong base in analytics allows professionals to explore advanced fields like artificial intelligence, natural language processing, deep learning, and automation.

    Advantages of Pursuing a Data Analytics Course

    • Learn High-Demand Skills: Equip yourself with core analytics abilities that are essential in today’s data-driven world.
    • Expand Career Options: Step into roles like Data Analyst, BI Analyst, Data Scientist, and other emerging positions.
    • Transform Data into Strategy: Understand how to analyze and convert raw data into actionable business insights.
    • Master Popular Tools: Get hands-on experience with platforms such as SQL, Python, Excel, Tableau, and Power BI.
    • Improve Earning Potential: Trained analytics professionals often earn competitive salaries and see faster career growth.
    • Work Across Sectors: Apply your skills in a wide range of fields, including healthcare, banking, e-commerce, and IT.
    • Strengthen Analytical Thinking: Enhance your ability to think logically, solve problems, and interpret complex data.
    • Gain Recognized Certification: Add credible, industry-approved certifications to your resume to increase job visibility.
    • Engage in Real Projects: Apply your learning through live projects and case studies that reflect real-world scenarios.
    • Step into Future Technologies: Use this course as a launchpad to explore AI, machine learning, and data science in depth.

    Popular Tools Commonly Utilized in Data Analytics

    • Python – A highly flexible programming language used for data analysis, machine learning, and visualization with popular libraries like pandas, NumPy, matplotlib, and seaborn.
    • R – A statistical programming tool often used in research and academic settings for deep statistical analysis and data visualization.
    • Microsoft Access – Best suited for smaller database tasks, offering quick data management and simple reporting features.
    • Tableau – A market-leading platform for creating interactive and insightful visual dashboards to communicate data stories effectively.
    • Power BI – A Microsoft-powered business analytics solution used to create rich reports and real-time dashboards from diverse data sources.
    • Looker – A modern data exploration tool from Google Cloud that allows real-time data analysis and user-friendly visualization.
    • Alteryx – An intuitive analytics platform known for its drag-and-drop workflow interface that supports data preparation and advanced analysis.
    • Google BigQuery – A fully managed, serverless data warehouse optimized for running fast queries on large datasets.
    • Azure Synapse Analytics – A unified analytics platform from Microsoft that blends big data processing with data warehousing for enterprise-grade insights.
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    Key Features

    ACTE Bangalore offers Data Analytics Training in more than 27+ branches with expert trainers. Here are the key features,

    • 40 Hours Course Duration
    • 100% Job Oriented Training
    • Industry Expert Faculties
    • Free Demo Class Available
    • Completed 500+ Batches
    • Certification Guidance

    Authorized Partners

    ACTE TRAINING INSTITUTE PVT LTD is the unique Authorised Oracle Partner, Authorised Microsoft Partner, Authorised Pearson Vue Exam Center, Authorised PSI Exam Center, Authorised Partner Of AWS.

    Curriculum

    Syllabus For Data Analytics Training in HSR Layout
    Module 1: Fundamentals of Data Analytics
    • Types of Data: Structured, semi-structured, and unstructured data.
    • Analytics Types: Descriptive, diagnostic, predictive, prescriptive.
    • Data Lifecycle: Collection, cleaning, analysis, visualization, interpretation.
    • Roles in Analytics: Data analyst, business analyst, data scientist.
    Module 2: Excel for Data Analysis
    • Formulas & Functions: SUM, IF, VLOOKUP, INDEX and MATCH.
    • Data Cleaning Tools: Remove duplicates, text-to-columns, data validation.
    • Pivot Tables: Summarize and explore large datasets
    • Charts: Column, bar, line, pie, combo charts for visualization
    Module 3: SQL for Data Querying
    • SELECT Queries: Retrieve specific data from tables.
    • JOINs: Combine data from multiple tables (INNER, LEFT, RIGHT)
    • GROUP BY & Aggregations: SUM, AVG, COUNT for grouped data
    • Subqueries & Aliasing: Use queries within queries and rename columns.
    Module 4: Python for Data Analytics
    • NumPy : Numerical computations and array handling
    • Pandas: Dataframes for reading, transforming, and analyzing data
    • Matplotlib: Basic charting and visualizations
    • Seaborn: Statistical data visualizations with styling options
    Module 5: Data Visualization Tools
    • Power BI: Microsoft’s business intelligence tool.
    • Tableau: Visual analytics platform for building dashboards.
    • Filters & Slicers: Interactive controls for data exploration.
    • Calculated Fields: Custom formulas within visuals
    Module 6: Basics of Machine Learning
    • Scikit-learn: Python library for machine learning.
    • Supervised Learning: Regression, classification (e.g., linear regression, decision trees).
    • Unsupervised Learning: Clustering techniques like K-Means.
    • Model Evaluation: Accuracy, confusion matrix, cross-validation.
    Module 7: Statistics for Data Analytics
    • Descriptive Statistics: Mean, median, mode, range, standard deviation
    • Probability: Basic probability, distributions, conditional probability.
    • Inferential Statistics: Hypothesis testing, confidence intervals, t-tests.
    • Environment Configuration: Set up ports, secrets and variables in hosting platforms.
    • Correlation and Regression: Relationships and prediction between variables.
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    Need customized curriculum?

    Get Hands-on Knowledge about Real-Time Data Analytics Projects

    Project 1
    Patient Readmission Analysis

    Predict which patients are likely to be readmitted using medical records and demographic data. Use machine learning models to identify key risk factors and patterns leading to readmissions.

    Project 2
    Disease Trend Analysis

    Visualize and analyze trends in disease spread over time and geography using public datasets. Leverage tools like GIS and time-series analysis to uncover hotspots and growth patterns.

    Project 3
    End-to-End Data Dashboard

    Build a full-stack dashboard using Power BI or Tableau to present company-wide KPIs. Combine data sources for interactive visuals and real-time insights.

    Project 4
    Data Cleaning & Transformation Pipeline

    Design a complete ETL pipeline using Python and SQL for raw-to-cleaned data conversion. Automate ETL with built-in error handling and logging.

    Launch Your Career with Expert Data Analytics Placement Support

    • Our Data Analytics Placement program is built to connect aspiring professionals with top organizations across industries like tech, finance, healthcare, consulting, and e-commerce.
    • We equip students with job-ready skills through mock interviews, technical training, and aptitude preparation, ensuring confidence in every stage of the hiring process.
    • Stay informed with real-time job alerts, interview notifications, and company updates via our dedicated Data Analytics Placement portal.
    • Our expert Data Analytics Placement team works closely with each learner to align their career goals with roles that match their strengths in data analytics.
    • With hiring partnerships ranging from startups to global enterprises, we offer a wide range of placement opportunities in high-demand analytics positions.
    • Our strong industry network and proven placement success reflect our commitment to helping students grow and succeed in the evolving analytics landscape.
    • We also offer post-placement support, including career mentorship and upskilling resources, to help students navigate their early professional journey and stay ahead in the fast-changing analytics field.

    Advance Your Career by Getting Your Data Analytics Certification

    A Data Analytics Certification can significantly strengthen your professional profile and open doors to a variety of high-demand roles in today’s data-centric job market. This credential demonstrates your proficiency in analyzing, interpreting, and visualizing data using industry-relevant tools like Python, SQL, Excel, Tableau, and Power BI. It highlights your ability to turn complex datasets into actionable insights that support smarter decision-making across diverse industries. Whether your goal is to work in analytics, BI, or data science, this certification gives you a competitive edge and access to exciting career opportunities.

    • Career Growth Opportunities
    • Stronger Market Appeal
    • Technical Proficiency
    While no certification can promise employment, earning a recognized Data Analytics credential greatly improves your job prospects. It showcases your readiness and skills, helping you stand out in a competitive hiring landscape.
    Basic familiarity with data concepts, statistics, and Excel is helpful. Some certifications are ideal for beginners, while others may require prior experience with SQL, Python, or BI tools. Hands-on work with datasets is a bonus.
    • Data Analytics Associate Certification
    • Business Intelligence Specialist
    • Professional Data Analyst
    • Advanced Analytics Certification
    • Data Analyst
    • Business Analyst
    • BI Developer
    • Reporting Analyst
    • Market Research Analyst
    • Product/Data Science (Entry-Level) Roles

    Complete Your Course

    a downloadable Certificate in PDF format, immediately available to you when you complete your Course

    Get Certified

    a physical version of your officially branded and security-marked Certificate.

    Get Certified

    Elevate Your Learning with Our Expert Data Analytics Trainers

    • Our Data Analytics Trainers are accomplished industry professionals with certifications and real-world project experience, bringing valuable knowledge into every session.
    • They’ve worked with leading organizations like Google, Amazon, IBM, Microsoft, and Deloitte sharing real-time case studies, practical techniques, and industry-standard practices.
    • Data Analytics Trainers training approach is interactive and learner-oriented, making complex subjects such as statistical analysis, data modeling, and dashboard creation easy to understand and apply.
    • Learners get hands-on experience using tools like Python, SQL, Power BI, Excel, and Tableau, ensuring they gain practical skills relevant to current industry demands.
    • Our curriculum is continuously updated to keep pace with the evolving tech landscape, preparing learners with the latest techniques and tools in data analytics.
    • Along with expert instruction, our Data Analytics Trainers provide career mentorship, personalized feedback, and placement guidance to help learners confidently step into high-impact analytics roles.
    • They also support learners in building strong portfolios and preparing for technical interviews, helping them stand out to employers in a competitive job market.

    Data Analytics Course FAQs

    Who are the course instructors, and how are they selected?

    At ACTE, all instructors are seasoned industry professionals with at least 10–12 years of relevant IT experience. Actively working in live corporate settings, they bring practical, current industry knowledge into the training. They are chosen for their knowledge, teaching skills, and practical experience to provide quality training with real-world applicability that meets the needs of the industry.
    Of course, ACTE offers practice tests developed to assist learners in assessing and consolidating knowledge and skills within the applicable domain. These tests are effective tools for monitoring progress and preparing for realistic applications.
    • ACTE is the Legend in offering placement to the students. Please visit our Placed Student list on our website.
    • We have solid working relationships with more than 700+ of the world's leading multinational corporations, including SAP, Oracle, Amazon, HCL, Wipro, Dell, Accenture, Google, ZOHO, TCS, IBM, and more.
    • More than 3500+ students placed last year in India & Globally. Our Placement Cell support you till you get placed in a better MNC.
    • Please Visit Your Student Portal. Here, the FREE Lifetime Online Student Portal helps you to access Job Openings, Study Materials, Videos, Recorded sections, & Top MNC Interview Questions.
    Yes, we offer job assistance upon course completion
    • Practical Experience
    • Hands-On Projects
    • Resume Preparation
    • Aptitude and Technical Skills
    • Mock Interviews
    • Group Discussions
    To enroll in ACTE's Data Analytics course, visit their website, navigate to the course page, and click Enroll Now. Fill out the form, choose your preferred batch timing, and start your Data Analytics journey today!
    The Data Analytics Master Program Training at ACTE provides in-depth knowledge of data analysis, visualization, and business intelligence. You will gain practical experience with tools such as Excel, SQL, Tableau, and Python to analyze, interpret, and visualize data. Through hands-on projects, you'll develop the skills to derive actionable insights and make informed decisions, equipping you for a successful career in data analytics and business intelligence.
    The ACTE certification validates abilities and knowledge in particular domains, which is valuable for career advancement. However, depending on employer preferences, industry norms, and how applicable the accreditation is for specific roles, its significance and recognition may differ.
    • A basic understanding of mathematics and statistics
    • Knowledge of Excel
    • Familiarity with databases
    • An understanding of business processes
    • Basic programming knowledge
    Indeed, many training programs are demanding as far as working on actual projects is concerned. More practical experience and a better understanding of the world and real lines actually give participants concrete skills, which enhances the employability of these trainees and readiness for professional roles.
    If you are unable to attend a class at ACTE, you can view recorded sessions or request make-up lessons. Additionally, resources and training materials are provided to help you compensate for missed content.
    Our course is easily manageable alongside your real-life commitments because it is available in customized one-on-one, fast-track, tailored, and online training modes.
    Learn Data Analytics at ACTE to take advantage of comprehensive training, an industry-standard curriculum, experienced instructors, real-world assignments, certification, assistance in obtaining employment, and a friendly learning environment that will ensure your success in the field.
    Yes, the Data Analytics classes will contain hands-on practice, real-world projects, and interactive discussions. They also include mock interviews and group discussions to improve your skills and prepare you for the job market. You will learn to solve technical issues properly and be successful in team-based settings.
    Yes, we give students lifetime access to the study materials, videos, and top MNC interview questions on the Student’s Portal.
    We offer recorded video lessons for the training. After you complete the payment and enroll in the course, you will gain access to the pre-recorded sessions through our course platform, allowing you to watch them at your own pace.
    The salary range for a Data Analytics professional is between 6 lakhs and 18 lakhs per year, and with increasing reliance on data-driven decisions, skilled analysts are seeing steady growth in demand and compensation.
    Yes, Learning Data Analytics is easy because of the various tools and resources available online with user-friendly interfaces. Most basic concepts are mathematical or statistical, logical, and learnable with some hands-on knowledge. Many also offer hands-on exercise programs with real-world projects where you can actually apply your learned knowledge.
    • Data Collection
    • Data Cleaning
    • Data Analysis
    • Data Visualization
    Yes, Data Analytics is the best option for freshers. The field is in hot demand across various industries globally. With more and more people focusing on data-driven decisions, there are many career opportunities. Thanks to the numerous courses, certifications, and resource availability, freshers easily acquire skills to succeed in this field.
    The primary use case for data analytics is to support a data-driven decision-making ecosystem across industries. It improves the optimization of business processes, customer experiences, and strategy refinement. Data analytics is particularly useful in domains such as marketing, healthcare, and finance, helping to reduce the risk of making unwise decisions and utilizing scarce resources efficiently.
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          Job Opportunities in Data Analytics

          More Than 35% Prefer Data Analytics for Business. Data Analytics Is One of the Most Popular and In-Demand Technologies in the Business World.

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          Data Architect
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          Upcoming In-Demand Jobs
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          Salary In Data Analytics

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