India’s No:1
DATA SCIENCE INTERNSHIP
KaaShiv Infotech offers, data science internship . Internship provides you an in-depth knowledge on Data Science . This internship enables the students to understand and learn the current trend in the job market. Students will prefer internships to build their profile for their jobs and also for their higher studies. Our company provides both offline and online data science internship . internship on Data Science imparts technical and programming skills on the below list of data science areas such as,
- Python Basics – Python Programming, Python Installation
- R- Programmming Introduction – Business Analytics, Data, Information , Compare R with other software in analytics
- Data Manipulation in R – Data sorting , Find and remove duplicates record , Cleaning data , Recoding data & its implementation
- Data Processing in Data Science – Data Processing techniques & its implementation
- Exploratory Data Analysis – Visualizing Data
- Statistical Analysis in Data Science – Median , Quartiles , Correlation , Covariance , Regression , Linear Regression , Non Linear Regression, Multiple Regression
- Web Scraping and Data Science Algorithm – Introduction to BeautifulSoup , Scraping data from Web , Data parsing
WHAT WE GIVE?
Certificates and Documents we offer for this Training
- Internship Certificate.
- Project Completion Certificate.
- Inplant Training(IPT) Certificate.
- Free Workshop Certificate.
- Free Corporate Training Test certificate.
- Training Documents.
- Sample Resume for Placement.
- Useful Softwares.
- Internship Report.
- Our AI Training Portal Access.
Why Internship is Important?
DATA SCIENCE INTERNSHIP
Learn by Doing
Put your skills to work on real projects, not just practice problems.
Find Your Passion
Try different areas of data science internship to see what clicks
Level Up Your Skills
Gain practical experience that will impress future employers
Boost Your Resume
Show employers you're serious and have what it takes
BEST COMPANY OFFERING DATA SCIENCE INTERNSHIP
Why to choose KaaShiv Infotech for
data science internship
The Course curriculum for data science internship is carefully researched and prepared by professionals from MNC to meet the demands expected in the current IT industries. After completing data science internship at KaaShiv Infotech, students will be familiar with the entire data science concepts. Below are some of the insights of our programme, data science internship.
data science internship
Short Term Internship ( data science internship )
Learn and Implement
45 Concepts Covering 7 Technologies
+ 2 Projects
Short Term - data science internship
- Data Science Internship Duration: 1 day, 2 days, 3 days, 5days/ 10days or Based on Student Preference
- Training hours: 3 hrs per day
- Software & other tools installation Guidance
- Hardware support
- Data Science Internship Report creation / Data Science Internship Project Report creation
- KaaShiv Infotech is top under, data science internship , 1 Real time projects – After 6 months of regular Paid Internship, Internship becomes free + For best interns Stipend will be provided + Best Interns will be offered Job too.
- Internship Certificate & Inplant Training Certificate & Industrial exposure certificate + (Achievement certificate for best performers)
S.No |
best data science internship – Syllabus100% Practical – Live HandsOn – data science internship |
---|---|
Topic 1 : | Python – Basics How Python code works with data science , DOWNLOAD & INSTALL PYTHON and data science libraries, (Python Data Science Tool – How to work ) |
Topic 2 : | What is R programming Business Analytics, Data, Information , Compare R with other software in analytics , Install R , Perform basic operations in R using command line , Learn the use of IDE R Studio , Use the ‘R help’ feature in R |
Topic 3 : | Introduction to R programming Variables in R , Scalars , Vectors , Matrices , List , Data frames |
Topic 4 : | What is Data Analytics – Data Manipulation in R Data sorting , Find and remove duplicates record , Cleaning data , Recoding data , Merging data , Slicing of Data , Merging Data , Web Scraping |
Topic 5 : | Data Processing in Data Science
Selecting rows/observations , Selecting columns/fields , Vectorized Processing , Split , Merging data , Relabelling the column names , Sorting , Optimized Data Processing , Groupby , Aggregate , Apply , Multiple functions for same data , Same function for multiple data , Multiple functions for multiple data |
+ Data Science Internship Certificate
+ Data Science Inplant Training Certificate
+ Free Industrial exposure certificate + (Achievement certificate for best performers) + 1 Data Science Projects
Learn and Implement
70 to 400 Concepts Covering 9 Technologies
+ 3 to 4 Projects
Long Term - data science internship
- Data Science Internship duration: 6 days to 6 Months or Based on Student Preference
- Training hours: 3 hrs per day
- Software & other tools installation Guidance
- Hardware support
- Data Science Internship Report creation / Data Science Project Report creation
- KaaShiv Infotech is top under, Data Science internship , based 2 real time projects.
- 3 Certificates will be given
- Internship Certificate
- Inplant Training Certificate
- Industrial exposure certificate
- + (Experience Letter for best performers and Researchers)
- Free Data Science Internship / Data Science internship free – data science 6 months internship – After 6 months of regular Paid Internship, Internship becomes free + For best interns Stipend will be provided + Best Interns will be offered Job too. Data Science internship salary – Will be paid after 6 months as stipend.
S.No |
summer data science internship 100% Practical – Live HandsOn – data science internship |
---|---|
Topic 1 : | Python – Basics What is Python?, Why Python?, Tuple, List, Dictionary ,Numpy Array , Numpy Matrix , Pandas Data Frame , Tools and Frameworks In Python , How Python code works with data science , DOWNLOAD & INSTALL PYTHON and data science libraries, Python Data Science Tool – How to work |
Topic 2 : | What is R programming Business Analytics, Data, Information , Compare R with other software in analytics , Install R , Perform basic operations in R using command line , Learn the use of IDE R Studio , Use the ‘R help’ feature in R |
Topic 3 : | Introduction to R programming Image Processing , Signal Processing ( HandsOn Image processing and Mathematical processing ) |
Topic 4 : | What is Data Analytics – Data Manipulation in R Data sorting , Find and remove duplicates record , Cleaning data , Recoding data , Merging data , Slicing of Data , Merging Data , Web Scraping |
Topic 5 : | Data Processing in Data Science
Selecting rows/observations , Selecting columns/fields , Vectorized Processing , Split , Merging data , Relabelling the column names , Sorting , Optimized Data Processing , Groupby , Aggregate , Apply , Multiple functions for same data , Same function for multiple data , Multiple functions for multiple data |
Topic 6 : | Exploratory Data Analysis – Visualizing Data Reading external csv file , Reading Options , Process read data , Writing csv file , Visualization , Histogram , Boxplot , Scatter Plot , Line Plot , Line chart , Pareto charts |
Topic 7 : | Statistical Analysis in Data Science Median , Quartiles , Correlation , Covariance , Regression , Linear Regression , Non Linear Regression, Multiple Regression , Model evaluation , Prediction using built model , clustering, Need for clustering , k-means clustering theory , Clustering is use case data , Visualization of clusters , dimensionality reduction , Eigen Value Decomposition , Principal Component Analysis , web scraping |
Topic 8 : | Web Scrapping and Data Science Algorithm Implementation Introduction to BeautifulSoup , Scraping data from Web , Data parsing , classification , k-nn classification theory , Naïve Bayes Classification theory , Decision Tree , Random Forest |
+ Data Science Internship Certificate
+ Data Science Inplant Training Certificate
+ Free Industrial exposure certificate + (Achievement certificate for best performers) + 2 Data Science Projects
Apply for data science internship
Contact Number / Whatsapp Number
- Mobile 1 : +91 7667662428
- Mobile 2 : +91 7667664842
- Mobile 3 : +91 9840678906
Email ID
5 DAYS – data science internship
DAY 1: data science internship
- Introduction Of Data Science.
- Data Science Environmental Setup
- Python – Basics
DAY 2: data science internship
- Introduction to R programming
- Business Analytics, Data, Information
- Compare R with other software in analytics , Install R
DAY 3: data science internship
- What is Data Analytics – Data Manipulation in R
- Data Processing in Data Science
- Multiple functions for same data , Same function for multiple data ,
- Multiple functions for multiple data.
DAY 4: data science internship
- Exploratory Data Analysis – Visualizing Data
- Reading external csv file , Reading Options ,
- Process read data , Writing csv file , Visualisation.
DAY 5: data science internship
- Statistical Analysis in Data Science
- Web Scraping and Data Science Algorithm Implementation
- Project Idea
- Project Work
What do data science interns do?
Core Responsibilities:
- Data Processing and Cleaning: You’ll likely assist with preparing data for analysis. This could involve tasks like:
- Importing data from various sources
- Handling missing values and inconsistencies
- Transforming data into a format suitable for analysis
- Exploratory Data Analysis (EDA): You might be involved in exploring and visualising data to understand trends, patterns, and relationships. This could involve:
- Creating charts and graphs
- Summarising data using statistical methods
- Identifying potential areas for further analysis
- Machine Learning : Kaashiv infotech provides machine learning models, there might be opportunities to get exposure to basic machine learning concepts through:
- Assisting with data preparation for machine learning models built by senior data scientists.
- Implementing simple machine learning algorithms for specific tasks under guidance.
Skills Developed During the Internship:
- Data analysis skills (using tools like Python)
- Data visualisation techniques
- Problem-solving and critical thinking
- Communication and collaboration skills
- Basic understanding of machine learning concepts (potentially).
Does data science require coding?
Yes, data science at Kaashiv infotech and in general does require coding. Here’s why:-
Machine Learning:
Even if the focus at Kaashiv infotech is on basic machine learning for interns, some level of coding is involved. This could involve: - Using libraries like scikit-learn (Python) to implement algorithms for tasks like classification or regression.
- Writing code to prepare data for machine learning models built by senior data scientists.
-
Data Visualization:
Creating data visualisations like charts and graphs is another core responsibility of data scientists. These visualisations are typically created using programming libraries like Matplotlib or Seaborn in Python.
-
Data Manipulation and Analysis:
A significant portion of a data scientist’s work involves preparing, cleaning, and analysing data. At Kaashiv infotech, their internship description mentions data processing and cleaning tasks that often rely on programming languages like Python.
Which language is used in data science?
Kaashivinfotech’s data science program, Python is likely the primary language used for data science tasksIndustry Standard:
Python is the most popular and widely used programming language in data science due to its readability, extensive libraries, and large community support. While Python is dominant, there’s a chance they might use other languages in specific situations:R:
R is another popular language used for statistical analysis and data visualisation. It’s less likely to be the primary language at Kaashiv infotech, but it might be used for specific tasks where R offers certain advantages.SQL:
SQL is a language used to interact with relational databases. Data scientists often need to extract data from databases for analysis, and SQL is the standard language for this purpose.- The specific language used for a particular project might depend on the project’s requirements and the preferences of the senior data scientists involved.
- If you’re interested in a data science internship at Kaashiv infotech, focusing on learning Python would be the most strategic approach, as it’s the most widely used and versatile language in the field.
- Once you have a strong foundation in Python, you can explore other languages like R or SQL to expand your skill set.
Is Python easy to learn?
Whether Python is easy to learn depends on your prior programming experience.For Beginners:
- Relatively Easy Compared to Other Languages: Python is often considered one of the easiest programming languages to learn, especially for beginners with no prior coding experience. This is because:
- Readability: Python’s syntax is known for being clear and concise, resembling natural language to some extent. This makes it easier to understand code structure and logic compared to languages with complex syntax.
- Focus on Functionality: Python prioritises readability and functionality over complex technicalities, making it easier to grasp core concepts without getting bogged down in the details.
Factors Affecting Ease of Learning:
- Prior Programming Experience: If you have experience with other programming languages, especially those with similar logic (like Java or C++), picking up Python will be considerably easier.
- Learning Resources: The abundance of online tutorials, courses, and beginner-friendly documentation makes learning Python accessible. Kaashiv infotech itself might offer some resources as part of their data science course.
- Dedication and Practice: Like any skill, mastering Python requires consistent practice and dedication. The more you code and experiment, the more comfortable you’ll become.
Here are some additional tips for learning Python:
- Start with the basics: Focus on understanding fundamental programming concepts before moving on to more complex topics.
- Practice coding regularly: The best way to learn Python is to write code yourself. There are many coding challenges and projects that can help you practise your skills.
Can a fresher become a data scientist?
It is possible for a fresher (someone with no prior work experience) to land a data science internship at Kaashiv infotech, but it might be challenging to secure a full-time data scientist position straight out of college.Data Science Internship:
- Kaashiv infotech Internship Program: They offer data science internships specifically aimed at freshers or students.
- Focus on Learning: These internships are likely designed to provide foundational knowledge and practical experience in data science.
- Skills Development: The internship can help you develop essential skills like data analysis, visualisation, and basic programming (likely using Python).
Challenges for Freshers in Full-Time Roles:
- Experience Requirement: Many full-time data scientist positions typically require some level of work experience (often 2-3 years) applying data science skills in real-world projects.
- Advanced Skills: Full-time roles often demand more advanced skills in areas like machine learning model development, data wrangling with complex datasets, and experience with various data science tools and libraries.
What Freshers Can Do:
- Internship is a Stepping Stone: A data science internship at Kaashiv infotech can be a great way to gain valuable experience and build your resume.
- Develop Skills: Focus on developing the necessary skills during your internship and through personal projects. Learn Python, data analysis techniques, and explore basic machine learning concepts.
- Network and Build Connections: Network with data scientists at Kaashiv infotech or other companies. These connections can be valuable sources of guidance and potential future opportunities.
FAQ'S
Data science internship FAQs: Frequently Asked Questions
Frequently Asked Questions: data science internship at KaaShiv Infotech
What do I need to know for a data science internship?
- Python Basics: This is likely their primary programming language.
- Data Analysis Skills: Learn data cleaning, manipulation, and visualisation techniques.
Basic Machine Learning Concepts: Understand fundamental algorithms for tasks like classification or regression.
What is the objective of a data analytics internship?
- For Kaashiv Infotech: Identify and nurture talent while gaining support for ongoing data analysis projects.
- For You (the Intern): Gain practical experience in data analysis and develop foundational skills for a data analytics career.
What is the main goal of a data analyst?
- Extract insights from data: This involves cleaning, organising, and analysing data to uncover hidden patterns and trends.
- Communicate findings: Data analysts present their insights in clear and concise ways, often through reports and visualisations, to inform business decisions.
What data science interns do?
- Cleaning and preparing data for analysis.
- Exploring data to find patterns and trends.
- Visualising data to communicate insights.
Is data science beginner friendly?
- Python is the main language: It’s known for being readable and beginner-friendly.
- Many resources exist: Online tutorials, courses, and communities can help you learn.
- Start with the basics: Focus on core concepts before diving into complex topics.
Is data science good for non IT students?
- Focus on skills, not background: Strong analytical thinking and problem-solving are more crucial than pure IT experience.
- Learn in-demand skills: Python, data analysis, and statistics are valuable across various fields.
Which sector is best for data scientist?
- The best sector for a data scientist depends on your interests, but some of the hottest fields right now are tech, finance, and healthcare! These sectors generate massive amounts of data that data scientists can analyse to solve important problems.
What is the career objective of a data science intern?
- A data science intern’s career objective is to leverage their technical skills and passion for data analysis to gain practical experience in building and applying data-driven solutions to real-world problems.