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(Class 1Hr - 1:30Hrs) / Per Session
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Overview of Data Analytics Online Training
Leranovita's data analytics course is a structured, all-inclusive training program that gives people the skills and information they need to do well in the area of data analytics. Participants in this course will learn how to gather, clean, preprocess, analyze, and show data using a variety of methods and tools. Usually, the program covers basic ideas in statistics, data mining, machine learning, and data visualization. This helps students learn more about how to make decisions based on data. Hands-on projects and case studies from the real world are often used to show how to use data analytics methods to solve complicated problems.
Get the Impactful Data Analytics Program:
- Data analytics is the process of looking at, changing, and making sense of a lot of information.
- In this Data Analytics course, you'll learn about the latest tools and techniques for analytics, as well as how to work with SQL databases and the languages R and Python.
- Data analytics courses often provide hands-on experience through practical assignments and real-world projects.
- These projects help learners develop critical analytical and problem-solving skills while gaining confidence in using data analytics tools effectively.
- Learn the most up-to-date methods and best practises that professionals in the field are using.
- Also, thorough instruction enables you to develop knowledge in this broad sector so that you can complete your daily activities with ease.
Data Analytics Development Trends and Techniques:
To keep up with the rising need for data-driven insights and decisions, data analytics development was accelerating. There may have been significant developments in the state of the art of data analytics since then. Some of the prevalent practices and approaches at the time are as follows:
AI and Machine Learning Integration: The use of artificial intelligence and machine learning in data analytics became more commonplace. In order to speed up model construction and enhance predictive analytics, we turned to automated machine learning (AutoML) techniques and methods.
Natural Language Processing (NLP): Using NLP methods, we were able to do sentiment analysis, language translation, and text mining on unstructured data types including text and speech.
Real-Time and Streaming Analytics: The need for instantaneous data has accelerated the development of streaming analytics applications. Apache Kafka and Apache Flink were two of the most popular technologies used by businesses for processing data in real-time.
Data democratization: A rise in the availability of data analytics to those who lack technological expertise. Independent data exploration was made possible by self-service analytics platforms and data visualization tools for usage by business users.
Big Data Analytics: In order to keep up with the ever-increasing influx of data in all its forms, businesses turned to big data analytics tools like Hadoop and Spark.
Advantages of Data Analytics:
- Decisions may now be made with more solid information rather than gut feelings, thanks to data analytics. It offers knowledge that may be used by leaders to make better choices.
- Data analytics may help businesses see trends, patterns, and correlations in their data. The information gleaned from these studies may provide light on consumer habits, market movements, and technological advances.
- Data analysis helps businesses find ways to improve their operations by reducing waste. Workflows may be streamlined and overall efficiency can be increased with the aid of data analytics.
- Data analytics allows for a more in-depth comprehension of clients, their preferences, and their requirements. Knowing what customers want allows businesses to better personalize their offerings and improve their marketing strategies.
- Organizations may use data analytics to provide consumers with more tailored services, which increases their pleasure and loyalty.
- With the use of data analytics, businesses can create predictive models to foresee prospective outcomes, look ahead to emerging trends, and spot untapped possibilities.
Tools used for Data Analytics:
The goal of data analytics is to get insights and aid in decision-making by means of processing, analyzing, and displaying data. varied analysts and businesses have varied requirements, hence there is a wide range of data analytics tools accessible. The following are examples of widely-used data-analysis tools:
Python: Python is a popular language for data scientists to utilize. NumPy, Pandas, Matplotlib, and Seaborn are just a few of the helpful tools it provides for working with and visualizing data.
R: R is another well-liked programming language for stats-heavy tasks like data analysis. There is a rich selection of tools and libraries available for use in data analytics projects.
Microsoft Excel: Microsoft Excel is a popular spreadsheet program that can do simple data analyses and provide visual representations for those who are not technically savvy.
Tableau: Tableau is a robust data visualization tool that enables users to build engaging dashboards and reports.
Power BI: Microsoft's Power BI is an enterprise analytics solution for producing reports and dashboards, analyzing and visualizing data, and modeling information.
Career Scope After Data Analytics Course:
When you graduate from a data analytics program, you'll be prepared to enter a variety of fields that value evidence-based decision making. The discipline of data analytics is expanding fast, creating need for qualified individuals who can analyze data, draw conclusions, and provide solutions for businesses throughout the world. After completing a data analytics course, you may look into the following employment options.
- In order to aid in decision-making, data analysts must acquire, cleanse, and analyze data. They employ several different data visualization and analytics techniques to ensure that the information they display is both engaging and informative.
- Data analytics is a key tool for today's business analysts as they examine current procedures, pinpoint areas for improvement, and recommend changes to increase efficiency and profitability.
- Business Analyst Data scientists use techniques like machine learning and statistical analysis to study large datasets, draw conclusions, and create forecasting models.
- To effectively convey data insights to stakeholders and support BI projects, business intelligence (BI) analysts create, deploy, and oversee dashboards, reports, and data visualizations.
- The goal of a marketing analyst is to help businesses make more informed strategic marketing decisions and to get their intended consumers more involved.
- Analysts in this field sift through mountains of data in search of patterns that might inform business and financial choices.
Top Skills You Will Gain
- Exploratory Data Analysis
- Data Visualization
- Statistical Modeling
- Data Mining
- Business Intelligence
- Data Warehousing
- Machine Learning
- Data Cleansing & Preparation
Data Analytics Course Key Features 100% Money Back Guarantee
5 Weeks TrainingFor Become a Expert
Certificate of TrainingFrom Industry Data Analytics Experts
Beginner FriendlyNo Prior Knowledge Required
Build 3+ ProjectsFor Hands-on Practices
Lifetime AccessTo Self-placed Learning
Placement AssistanceTo Build Your Career
Top Companies Placement
Annual SalaryHiring Companies
Data Analytics CourseCurriculam
Data analytics trainers generally have hands-on expertise. They may have been data analysts, scientists, business intelligence analysts, or other data-related professionals in finance, healthcare, marketing, or technology.
Syllabus of Data Analytics Online Course Download syllabus
- Descriptive Analytics
- Diagnostic Analytics
- Predictive Analytics
- Prescriptive Analytics
- Types of Data
- Relational Databases
- Primary Key and Foreign Key
- SQL Select Queries
- Null and Data Types
- JOIN To Query Multiple Tables
- Operators and Functions
- Data Aggregations
- Microsoft Excel fundamentals
- Excel pivot tables
- Conditional function
- Lookup functions
- Data Analysis Tool
- Data Normalization in Python
- Data Binding with Python
- Data Formatting with Python
- Model Development and Customization
- Correlation and GroupBy
- Data Visualization
- Working with Dimensions
- Data Management Filters
- Filters in Detail
- Advance Visuals and Features in Tableau
- Getting and Transforming Data in Power Bi Desktop
- Modeling with Power BI
- DAX Function
- Visualization of Data
- Publishing Reports
- ER Diagram
- Schema Design
- SQL SELECT and its Functions
- SQL JOIN and its Function
- SQL views and constraints
- SQL DDL and DML operation
- Creating data for analytics through designed experiments
- Creating data for analytics through Active learning
- Creating data for analytics through Reinforcement learning
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Exploratory Data Analysis
Explore a dataset. Descriptive statistics, data cleaning, and pertinent charts and graphs provide insights and patterns.
Use facts to create a prediction model. Decision trees, logistic regression, and linear regression may forecast customer turnover, product sales, and stock prices.
Customer segmentation analyzes customer preferences, behaviors, and traits. K-means or hierarchical clustering customer profiles.
- Mock interviews by Learnovita give you the platform to prepare, practice and experience the real-life job interview. Familiarizing yourself with the interview environment beforehand in a relaxed and stress-free environment gives you an edge over your peers.
- Our mock interviews will be conducted by industry experts with an average experience of 7+ years. So you’re sure to improve your chances of getting hired!
How Learnovita Mock Interview Works?
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Data Analytics Training Objectives
- Learning how to analyze and understand massive volumes of data to drive business choices is a key objective of the Data Analytics Certification course. The methods, tools, and processes currently employed in the field of data analytics are discussed in depth throughout this course.
- Understanding the fundamentals of data analytics and its applications
- Learning various data analytics techniques and tools
- Gaining proficiency in data cleaning, manipulation, and analysis
- Developing skills in data visualization and reporting
- Understanding predictive modeling and machine learning algorithms
- Applying data analytics concepts to real-world scenarios and projects
- Data analytics has a wide range of potential applications that are only anticipated to expand. There is a rising need for skilled people who can analyze and draw insights from data to help decision-making as the volume of data created by enterprises continues to rise. Finance, medicine, the retail sector, the marketing and sales sectors, and more may all benefit from data analytics.
- Big Data Analytics: The processing and analysis of enormous amounts of data to provide insightful results.
- Making forecasts and automating decision-making processes with machine learning and artificial intelligence.
- Real-time analytics: Analyzing data as it is happening to inspire quick reactions and actions.
- Ensuring the ethical and secure management of data is data privacy and security.
- Developing interactive and dynamic visuals for enhanced data interpretation is known as advanced visualization.
- Skills in data analytics are highly sought-after by employers. Data analysts and data scientists are in greater demand across sectors as businesses depend more and more on data-driven decision-making.
- Work on real-world datasets available online or provided by the training program.
- Utilize data analytics tools such as Python with libraries like Pandas, NumPy, and Scikit-learn, or R with packages like dplyr and ggplot2.
- Collaborate on data analytics projects with peers or join online communities to gain insights and feedback.
- Data Analyst
- Data Scientist
- Business Intelligence Analyst
- Data Engineer
- Data Architect
- Data Visualization Specialist
- Data Analyst Manager
- Machine Learning Engineer
- Predictive Analyst
- Data cleaning, transformation, and manipulation techniques.
- Statistical analysis and hypothesis testing.
- Predictive modeling and machine learning algorithms.
- Understanding of databases and SQL.
- Problem-solving and critical thinking in the context of data analysis.
- Due to the growing significance of data-driven decision-making in enterprises, the Data Analytics Course is necessary. Professionals may get important insights that promote corporate development and success by being able to evaluate and comprehend data.
- Basic knowledge of statistics and maths.
- SQL and database expertise.
- Strong problem-solving and analytical abilities.
- Knowledge of data visualization software is advantageous.
Data Analytics Course & Certification
- Career opportunities and improved job prospects.
- Industry recognition and validation of skills.
- Access to higher-level roles and responsibilities.
- Potential for higher earnings compared to non-certified peers.
- Demonstrates commitment to growth and learning.
Begin by thoroughly understanding the exam's content, objectives, and format. Assess your existing knowledge and skills in data analysis, identifying your strengths and areas that require more attention.
- Certified Analytics Professional (CAP)
- Microsoft Certified: Data Analyst Associate
- IBM Data Science Professional Certificate
- Google Data Analytics Professional Certificate
- SAS Certified Data Scientist
Data Analytics certifications demonstrate your expertise and commitment to potential employers, making you a more competitive candidate. Certifications enhance your chances by validating your proficiency, but practical experience, a strong resume, and effective job search strategies are also crucial.
- Statistical Analysis
- Data Visualization
- Data Manipulation
- Programming Languages (Python, R)
- SQL and Database Management
Pranav SrinivasSoftware Testing, Capgemini
Data Analytics Course FAQ's
- LearnoVita will assist the job seekers to Seek, Connect & Succeed and delight the employers with the perfect candidates.
- On Successfully Completing a Career Course with LearnoVita, you Could be Eligible for Job Placement Assistance.
- 100% Placement Assistance* - We have strong relationship with over 650+ Top MNCs, When a student completes his/ her course successfully, LearnoVita Placement Cell helps him/ her interview with Major Companies like Oracle, HP, Wipro, Accenture, Google, IBM, Tech Mahindra, Amazon, CTS, TCS, HCL, Infosys, MindTree and MPhasis etc...
- LearnoVita is the Legend in offering placement to the students. Please visit our Placed Students's List on our website.
- More than 5400+ students placed in last year in India & Globally.
- LearnoVita Conducts development sessions including mock interviews, presentation skills to prepare students to face a challenging interview situation with ease.
- 85% percent placement record
- Our Placement Cell support you till you get placed in better MNC
- Please Visit Your Student's Portal | Here FREE Lifetime Online Student Portal help you to access the Job Openings, Study Materials, Videos, Recorded Section & Top MNC interview Questions
- LearnoVita Certification is Accredited by all major Global Companies around the World.
- LearnoVita is the unique Authorized Oracle Partner, Authorized Microsoft Partner, Authorized Pearson Vue Exam Center, Authorized PSI Exam Center, Authorized Partner Of AWS and National Institute of Education (nie) Singapore
- Also, LearnoVita Technical Experts Help's People Who Want to Clear the National Authorized Certificate in Specialized IT Domain.
- LearnoVita is offering you the most updated, relevant, and high-value real-world projects as part of the training program.
- All training comes with multiple projects that thoroughly test your skills, learning, and practical knowledge, making you completely industry-ready.
- You will work on highly exciting projects in the domains of high technology, ecommerce, marketing, sales, networking, banking, insurance, etc.
- After completing the projects successfully, your skills will be equal to 6 months of rigorous industry experience.
- We will reschedule the classes as per your convenience within the stipulated course duration with all such possibilities.
- View the class presentation and recordings that are available for online viewing.
- You can attend the missed session, in any other live batch.