Online Classroom Batches Preferred
Weekdays Regular
(Class 1Hr - 1:30Hrs) / Per Session
Weekdays Regular
(Class 1Hr - 1:30Hrs) / Per Session
Weekend Regular
(Class 3hr - 3:30Hrs) / Per Session
Weekend Fasttrack
(Class 4:30Hr - 5:00Hrs) / Per Session
No Interest Financing start at ₹ 5000 / month
Skills You Will Gain
- Big Data, HDFS
- YARN, Spark
- MapReduce
- PIG, HIVE
- Mahout, Spark MLLib
- Solar, Lucene
- Zookeeper
Data Science Course Key Features 100% Money Back Guarantee
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5 Weeks Training
For Become a Expert -
Certificate of Training
From Industry Data Science Experts -
Beginner Friendly
No Prior Knowledge Required -
Build 3+ Projects
For Hands-on Practices -
Lifetime Access
To Self-placed Learning -
Placement Assistance
To Build Your Career
Top Companies Placement
A professional application developer is an irreproachable source code creator of the software. Technoscientifically, application developers involves in the end-to-end software development life cycle. They create, test, deploy, and help to upgrade software as per the requirement of clients. They are often rewarded with substantial pay raises as shown below.
- Designation
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Annual SalaryHiring Companies
Data Science Course Curriculam
Trainers Profile
Trainers are certified professionals with 11+ years of experience in their respective domains as well as they are currently working with Top MNCs. As all Trainers from Data Science Course Online Training course are respective domain working professionals so they are having many live projects, trainers will use these projects during training sessions.
Pre-requisites
Following is sufficient for basics of Data Science technologies :
Syllabus of Data Science Online Course Download syllabus
- Introduction to Data Science
- Data Science Terminologies
- Classifications of Analytics
- Data Science Project workflow
- Data engineering importance
- Ecosystems of data engineering tools
- Core concepts of data engineering
- 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
- Visualization Packages (Matplotlib)
- Components Of A Plot, Sub-Plots
- Basic Plots: Line, Bar, Pie, Scatter
- Advanced Python Data Visualizations
- R Installation and Setup
- R STUDIO – R Development
- R language basics and data structures
- R data structures , control statements
- Important statistical concepts used in data science
- Difference between population and sample
- Types of variables
- Measures of central tendency
- Measures of variability
- Coefficient of variance
- Skewness and Kurtosis
- Data visualization
- Missing value analysis
- The correction matrix
- Outlier detection analysis
- Introduction to Azure ML studio
- Data Pipeline and ML modeling with Azure
- MS Excel core Functions
- Pivot Table
- Advanced Functions
- Linear Regression with Excel
- Goal Seek Analysis
- Introduction of cloud
- Difference between GCC, Azure, AWS
- AWS Service ( EC2 and S3 service)
- AWS Service (AMI), AWS Service (RDS)
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Industry Projects
Mock Interviews
- 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?
Data Science Training Objectives
- A Data Science certification course is a structured program designed to provide individuals with the necessary knowledge and skills in Data Science. These courses cover various topics such as statistics, programming, machine learning, data visualization, and more. By completing a Data Science Certification course, individuals can demonstrate their proficiency in Data Science concepts and techniques, which can enhance their job prospects and career growth in the field.
- The scope of Data Science is expected to expand significantly in the future. With the exponential growth of data and the increasing adoption of data-driven decision making, organizations across industries will continue to rely on Data Scientists to extract valuable insights from data. The application areas of Data Science, such as personalized marketing, fraud detection, recommendation systems, healthcare analytics, and predictive maintenance, are likely to grow further.
- Data scientist.
- Data analyst.
- Data engineer.
- Data architect.
- Business analyst.
- Explainable AI: The ability to interpret and explain the decisions made by AI models.
- Automated Machine Learning: Tools and techniques that streamline the process of building and deploying machine learning models.
- Edge Computing: Performing data processing and analysis at the edge devices instead of relying solely on the cloud.
- Ethical AI: Incorporating ethical considerations and responsible practices into AI development and deployment.
- Set up a development environment: Install the necessary software, such as Python or R, along with libraries and packages commonly used in Data Science.
- Access datasets: Find datasets that align with your interests or industry domains. You can explore publicly available datasets or use datasets provided in online learning platforms.
- Work on projects: Choose projects that involve tasks like data cleaning, exploratory data analysis, predictive modeling, or data visualization. Implement algorithms, build models, and analyze the results.
- Join online communities: Participate in online forums, discussion boards, and Data Science communities where you can share your work, seek feedback, and learn from others.
- Data scientist.
- Data analyst.
- Machine learning engineer.
- Business analyst.
- Data engineer.
- Statistics and mathematics for data analysis.
- Data manipulation, cleaning, and preprocessing techniques.
- Machine learning algorithms and techniques.
- Model evaluation and validation techniques.
- Working with databases and SQL.
- Basic knowledge of mathematics and statistics.
- Understanding of data structures and algorithms.
- Some exposure to machine learning concepts (recommended but not mandatory)
- Data Science professionals are typically well-compensated due to the high demand for their skills. According to industry reports, the average salary of a Data Scientist can range from $80,000 to over $150,000 per year.
- Yes, the Data Science course is unique due to its significance and continuing relevance in the data-driven world of today. Industry-changing data science has the capacity to encourage innovation while tackling challenging problems. You might contribute to ground-breaking research, develop innovative approaches, and have a significant effect in a wide range of fields through improving your data science capabilities.
Exam & Certification
- Participate and Complete One batch of Data Science Training Course
- Successful completion and evaluation of any one of the given projects
- Complete 85% of the Data Science course
- Successful completion and evaluation of any one of the given projects
- Oracle Certified Associate (OCA)
- Oracle Certified Professional (OCP)
- Oracle Certified Expert (OCE)
- Oracle Certified Master (OCM)
- Learn About the Certification Paths.
- Write Code Daily This will help you develop Coding Reading and Writing ability.
- Refer and Read Recommended Books Depending on Which Exam you are Going to Take up.
- Join LearnoVita Online Training Course That Gives you a High Chance to interact with your Subject Expert Instructors and fellow Aspirants Preparing for Certifications.
- Solve Sample Tests that would help you to Increase the Speed needed for attempting the exam and also helps for Agile Thinking.
Recently Placed Students
Pranav Srinivas
Software Testing, CapgeminiData Science Course FAQ's
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- 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.