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 with Python Course Key Features 100% Money Back Guarantee
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5 Weeks Training
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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.
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Data Science with Python 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 with Python Certification 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 with Python technologies :
Syllabus of Data Science with Python Online Course Download syllabus
- What is Data Science?
- What does data science involves?
- Life cycle of Data Science
- Tools of Data Science
- Introduction to Python
- Introduction to python
- Software installation
- Basic operators and functions
- Data types with python
- Conditional statement
- Introduction to Numpy
- Introduction to numpy arrays
- How to Access Array Elements?
- Indexing, Slicing, Iteration, Indexing with Boolean Arrays
- Measures of Central Tendency
- Measures of Dispersion
- Descriptive Statistics
- Probability Basics
- Marginal Probability
- Bayes Theorem
- Probability Distributions
- Hypothesis Testing
- Understand Time Series Data
- Visualizing Time Series Components
- Exponential Smoothing
- Holt's Model
- Holt-Winter's Model
- Introduction to Pandas
- Defining data structures
- Understanding Dataframes
- Importing Data from various sources
- Missing values
- Data Operations
- File read operations
- Descriptive statistics
- Create plots like scatter plot
- Histogram, Bar graph, Pie chart using Matplotlib Grids
- Machine learning Process Flow
- Machine learning categories
- Feature selection and extraction in machine learning
- Supervised learning algorithms
- Simple linear Regression
- Applications of linear regression
- Building regression models using python
- Process to implement linear regression
- Coefficient of determination (R- Squared)
- Accuracy of model
- Multiple linear Regression
- Parsing HTML and XML
- Navigating the document
- Handling CSV files
- Parsing JSON into Python
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- 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.
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Data Science with Python Training Objectives
- The Data Science with Python certification course is designed to provide comprehensive training in data science using Python programming language. It covers various aspects such as data cleaning, data visualization, statistical analysis, machine learning, and predictive modeling using Python libraries like NumPy, Pandas, Matplotlib, and scikit-learn. The course aims to equip participants with the necessary skills to solve real-world data science problems using Python.
- The future potential for Data Science utilising Python are expected to be favourable. Firms are on the lookout for professionals who can effectively examine and comprehend data since there has been an increasing demand for data-driven decision making and a boost in the availability of data. Python has become a popular choice for projects involving data science because of its flexibility, large library, and simplicity of use. As a result, there is a growing demand for Python-trained data scientists, which points to a bright prospect for the future.
- Data Science with Python is indeed a trend that is leading the tech industry. Python's simplicity, versatility, and extensive libraries for data science have contributed to its widespread adoption. With advancements in machine learning, artificial intelligence, and big data analytics, Python is well-suited to handle complex data science tasks. As more industries embrace data-driven approaches, the demand for Python-based data science solutions is expected to grow.
- To practice Data Science with Python, you can set up a local development environment on your computer using Python IDEs like Anaconda, Jupyter Notebook, or PyCharm. These IDEs provide an interactive environment for writing and executing Python code, visualizing data, and building machine learning models. You can also leverage online platforms and datasets to practice real-world data science projects.
- Data scientist.
- Data analyst.
- Machine learning engineer.
- Data engineer.
- Business analyst.
- Data cleaning and preprocessing techniques.
- Exploratory data analysis and visualization.
- Statistical analysis and hypothesis testing.
- Machine learning algorithms and techniques.
- Model evaluation and validation.
- Providing a solid understanding of data science concepts and techniques.
- Equipping participants with practical skills in using Python for data analysis, visualization, and modeling.
- Familiarizing participants with popular Python libraries and tools for data science.
- Enabling participants to apply data science methodologies to solve real-world problems.
- Preparing participants for industry-recognized certification in Data Science with Python.
- The salary of a Data Science with Python developer can vary based on several factors such as experience, skills, location, industry, and the organization they work for. Data Science professionals with Python skills are often well-compensated, with salaries ranging from moderate to high, depending on their expertise and the demand for data science talent in the job market.
- Yes, Python-based Data Science is considered as a technical skill. In order to extract knowledge as well as value from data, programming languages, statistical techniques, and machine learning algorithms are implemented. Python is an essential skill for data professionals because it is commonly utilised in IT industries for data science operations.
- Basic understanding of programming concepts (Python knowledge is beneficial but not always mandatory)
- Familiarity with statistics and mathematical concepts.
- Good analytical and problem-solving skills.
- Eagerness to learn and apply data science techniques.
- Access to a computer with the necessary software and tools for Python programming and data analysis.
Exam & Certification
- Participate and Complete One batch of Data Science with Python Training Course
- Successful completion and evaluation of any one of the given projects
- Complete 85% of the Data Science with Python 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.

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Software Testing, CapgeminiData Science with Python Course FAQ's
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- All training comes with multiple projects that thoroughly test your skills, learning, and practical knowledge, making you completely industry-ready.
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