SUMMER INTERNSHIP for B.Tech

  • Summer Internship B.Tech

COMPLETE TRAINING ON TECHNOLOGY | PROJECT DEVELOPEMENT


Training Fee

Rs.6500 /-

May June July

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Contact Us

MANOJ: +91 9676190678

HYDERABAD

407, 4th Floor, Pavani Prestige (R.S Brothers)Building, Ameerpet, Hyderabad, India Opposite Image Hospital & Beside KLM Fashion Mall.

About Summer Internship B.Tech

Any internship will let you know in detail about the kind of field you want to excel in. The B Tech Summer Internships at Tru Projects are provided every year thus helping as many students as possible. The Summer Internship for b tech students at our company will give you an industry level introduction as to how big companies in multiple industries function. We have many varieties of internships available for you. Finding Student Internship Opportunities for b tech students is always a hassle but not at TruProjects. For instance just for the summer time we have a diverse category of internships. The Summer Internship Programme for b tech students will help you majorly if you are currently pursuing your bachelor degree in technology. You will find that our Online Summer Internship Institute for b tech students will let you operate and work from your own home at your convenience. Obviously apart from that you will gain a lot of knowledge and work with differently skilled professionals and interact with other students as well by doing our Online Summer Internship Program for b tech students. This Student Summer Internship for b tech students is likely to enhance your existing skill set to an even better one thus helping you to become a trained candidate as well.

When we say training, it means that your capabilities are honed both in the practical field as well as theoretically. You not only learn the fundamental concepts but also the complex and important factors in the Summer Internship for Students for b tech students. It is true when they say learning new skills is necessary, as you are aware of the amount of competition that exists today given any field in B tech. By doing the Summer Internship Training for b tech students at TruProjects, you will always be a step ahead than your peers. Our institute offers a unique IT Summer Internship for b tech students too. This particular internship will target the concepts in the IT sector, hence letting you become an expert especially if you are a student from the IT Branch. Our Summer Intern Openings for b tech students is conducted every year where we see curious minds use their creative skills to further improve themselves. Usually during the summer, everyone spends their time doing fun activities but what if you could also learn in a fun way by spending minimal time in a day? Sounds impossible right?

But yes! Our Online Summer Internship for b tech students is the answer. You can now develop new skills by putting efforts every day in our online Summer Internship with certificate for b tech students and still have fun during your summer holidays. Another popular internship is our Software Engineering Summer Internship for b tech students. We see students from many different branches who come asking us if they could shift to software engineering and get a job. We tell you that it is absolutely possible. An even better thing is that our Software Development Internship for b tech students will help you understand everything you need to. The Software Engineering Internship for b tech students will allow you to start working on beginner projects and move on to advanced ones as soon as you are able to grasp the concepts. If you are searching for companies to work as a Software engineer intern for b tech students or a Software Development Engineer Intern for b tech students then TruProjects is the right place for you. Moreover the Software Development Engineer Internship for b tech students is likely to be of great value to you in the future as it allows you to work in such an environment at an early stage as a student. Undoubtedly the Software Engineering Internship Program for b tech students is helpful to students in numerous ways such as working with supervisors and also being able to contribute to our company. We highly encourage you to choose our Software Engineer Summer Intern for b tech students if you feel that software interests you. Our Virtual Summer Internship for b tech students is to make sure our students are able to be an intern even via the internet. They need not be physically available in order to do the work. Students in their last year should be aware of the importance of an internship by now. If you are in search of Internship for final year students for b tech students then call us right away. If you wish to learn in depth before applying for jobs, you can always choose our Summer Final Year Internship for b tech students.

The Final Year Summer internships for b tech students is designed specifically for final year students as they majorly apply for companies in the tech industry. Students will be trained accordingly in batches. We at TruProjects advise students to make use of any Student Internship Opportunities for b tech students you come across. The Internship Program for b tech students usually help students to know what they are supposed to learn and what to skip. Strategizing better for your career goals is definitely one of the main benefits you obtain by doing our Internship Training Program for b tech students. And we always thrive to be the Best Internship Training Institute for b tech students and be of help as much as we can. There are also Internship certificate Training for b tech students available at Tru Projects. The obtained certificate will be of huge value especially when you create your resume for future purposes. Finding good internships for Freshers for b tech students is very hard to find, but you can find it at one place, at our company. Biggest win is that you will have access to also make it as an Online Internship Training Program for b tech students as well. You will be able to have this option for many other internships available, therefore providing you flexibility at its best. Another advantage of the online Internship for engineering is that you can handle your college academics and also learn and work for us at a manageable time.

It is definitely an understandable request when students want Best longterm Internship Training for b tech students. We too feel it’s important enough as the Longterm Internship Training for b tech students allows us to train our students in an even better way with adequate time. Also with the help of the Long Term Internship Program for b tech students, we can understand the students needs and guide them in the long run. Many graduates and sometimes even ongoing students seek Professional Internship for b tech students. Based on their targets, goals and future aspirations, we assign them work and mentors to help them. A lot of the students look forward to any paid Internship for engineering students for b tech students. This is also what you will find at Tru Projects. The real time summer Internship for b tech students will help the students to gain not only knowledge as mentioned before but also confidence and self belief. We make sure that the mentors make the students comfortable during their real time summer Internship program for b tech students. Especially during the Online Internships for students for b tech students, all our mentors interact with every student and make sure they are grasping all the lessons taught as well. You can choose our Full Time Summer Internship Program for b tech students or even our Full Time Paid Summer Internship for b tech students. Like mentioned before, you have a plethora of options to choose from. The Summer College Student Internship for b tech students is that you gain valuable experience which will help you plan your career properly.

Long Term Internship Opportunity for b tech students is mostly available for many internships, you can contact us for further information regarding it. Like mentioned above, the Summer Internship Training Course for b tech students will help us explore the different pathways in the industries. You can also opt for the Online Summer Internship Training for b tech students option and work accordingly. One of the popular internships is our Programming Internships for b tech students. Students over the years have found our Internship Program For Graduate for b tech students very helpful as it helps them develop their coding skills. All the core concepts of programming are covered from the starting in our Internship Program For Fresher for b tech students. Another unique internship is our Summer Analyst Internship for b tech students. This internship will equip you with the needed training regarding data analytics in detail. You will find our summer Internship for undergraduates for b tech students very interesting. The training will be filled with involvement in multiple areas hence making it easier for you to know your interests. The Summer Research Internship for b tech students allows you to research in depth about your needed domain.

It is often researchers who analyse the positives and negatives which help us rectify what we can. It is truly one of the most unique internships at Tru Projects. If you wish to pursue research oriented roles in the future, our Summer Research Internship Program for b tech students is the best choice for you. You will be able to understand which specialisation you are inclined towards and build hands-on skills with our research Internships for undergraduates for b tech students. It is such a challenge to find an Engineering Internship Program for b tech students in India. But at TruProjects you have so many options especially with our Summer Technical Internship Program for b tech students. Also our Certification Internship Undergraduates for b tech students will grant you a certificate at the end of your time at the company. You can use this certificate to boost your chances at landing good jobs. By being a part of the Paid Certification Summer Internship for b tech students, you will be given the choice of earning money while your time as an intern at the company.

Students can also seek Paid Programming Summer Internship for b tech students is also available at Tru Projects. The Paid Summer Internship Programme for b tech students allows them to learn programming at a higher level while earning. We find that the Intern Programme b tech Students for b tech students is more suitable for students who wish to learn coding with utmost sincerity. As we all know programming needs students to put their problem solving skills to their best, the intern Programme Undergraduates for b tech students will help them create their own ideas. You will have many options to choose from such as The Paid Summer Intern Programme for b tech students or the Programming Intern Undergraduates for b tech students. So if you want to increase your analytical and logical thinking skills, you can also opt to choose the role of Paid Programming Summer Intern for b tech students We work hard everyday to provide the best computer science internship for b tech students and different types of internships as well which are beneficial to students from multiple departments and places.

Internship Tracks

Machine Learning

Day - 1: Introduction to Machine Learning
1. Introduction to Machine Learning.
2. How Machine Learning Useful in Daily Life
3. Machine Learning Goals and Deliverables.
4. Why Machine Learning
5. Machine Learning Tools.
Programming Essentials
Day - 2: Introduction to Python
1.Introduction to Python
2.Anaconda Installation and Introduction to Jupyter Notebook
Day - 3: Python Basics
1. Data Structures in Python (Lists, Tuples, Dictionaries, sets)
Day - 4: Python Baiscs
1.Loops, conditional arguments, Comprehensions, Inbuilt functions , string manipulation etc.
Day - 5: Python Baiscs
1.Introuction to OOPS, Inheritence,Polymorphism,Encapsualtion,Abstraction
Day - 6: Python for Data Science - Numpy
1. Introduction to Numpy.
2. Operations in Numpy
Day - 7: Python for Data Science - Pandas
1. Introduction to Pandas.
2. Operations in Pandas – Pandas Basics, Indexing and selecting Data,Merge and Append, Grouping and Summarizing, Lambda functions and Pivot tables
3. Introduction to Reading.
Day - 8: Python for Data Science - Matplotlub
1. Introduction to Matplotlib.
2. Types of plots with ExamplesInheritence,Polymorphism,Encapsualtion,Abstraction
Day - 9: Introduction to SQL
1. Introduction to Database design,.
2. Basics of SQL, Data Retrieval, sorting, compound functions and relational operators, pattern matching with wild cards.
3. Basics on Table creation, updating, modifying etc.
4. Overall Structure of data retrieval queries, Merging tables, User Defined Functions (UDF), Frames.
Statistics & Exploratory Data Analysis (EDA)
Day - 10: Introduction to Data Analytics
1. Business and Data Understanding
2. CRISP-DM Framework – Data Preparation, Modelling, Evaluation and Deployment
Day - 11: Data Visualization in Python
1.Introduction to visualization and Importance of Visualization
2. Introduction to various charts
3. Data visualization toolkit in Python (Libraries or modules available in Python)
4. Plotting Data in Python using matplotlib and seaborn – Univariate Distributions, Bi-variate Distributions
5. Plotting Time series data
Day - 12: Exploratory Data Analysis
1. Introduction to Data Sourcing and various sources available for data collection
2. Data Cleaning – Fixing rows and columns, Missing value Treatment, standardizing values, handling invalid values, Filtering data
Day - 13: Exploratory Data Analysis
1. Data types – Numerical, Categorical (ordered and unordered)
2. Univariate Analysis, Bivariate Analysis, Segmented univariate Analysis
3. Derived Metrics and Feature Engineering
Day - 14: Exploratory Data Analysis
1. Introduction to Outliers.
2. Identify Outliers
3. Outliers Handling using Imputation Techniques
Day - 15: Inferential Statistics
1. Introduction to inferential statistics – basics of probability, Random Variables, Expected value, Probability Distributions
2. Discrete and Continuous Probability Distributions
3. Central Limit Theorem – Introduction and Industrial applications
Day - 16: Hypothesis Testing
1. understanding Hypothesis Testing, Null and Alternate Hypothesis, Industry Relevance
2. Concepts of Hypothesis Testing – p value method, critical value method
3. Types of Errors, T Distribution, other types of tests
4. Industry Demonstration and A/B Testing
Day - 17: Case Study
1. Credit Analysis EDA
2. GDP EDA Analysis
Machine Learning - I
Day - 18: Introduction to Machine Learning
1. Introduction to Machine Learning – Supervised and Unsupervised learning Methods
Day - 19: Simple Linear Regression
1. Introduction to Regression and Best Fit Line
2. Assumptions of Linear Regression (LINE)
3. Cost Functions, Strength of Linear relationship – OLS, coefficient of correlation, coefficient of Determination
4. Intuition to Gradient Descent for optimizing cost function
5. Hypothesis Testing in Linear Regression
6. Building a Linear Model – Reading Data, Cleaning Data, Libraries available – Sklearn, Statsmodel.api
7. Model Building using Sklearn and Training and Test Data, Model Development, Model validation using Residual Analysis, Evaluation against the test Data
Day - 20: Multiple Linear Regression
1. Using Multiple Predictors for Linear Regression
2. Introduction to overfitting, Multi-collinearity
3. Dealing with Categorical variables – OHE, Dummies, Label Encoding
4. Building the model using statesmodel.api and importance of p-values
5. Model Evaluation Metrics – Coefficient of Determination, Adjusted R2, RMSE, AIC, BIC and other model evaluation Metrics
6. Variable Selection – RFE, Step wise selection etc.
7. Gradient Descent and Normal Equation for Multiple Linear Regression
8. Industry Demonstration: Linear Regression Case Study
Day - 21: Logistic Regression
1. Introduction to Classification
2. Binary classification using univariate logistic regression
3. Maximum Likelihood function, Sigmoid Curve and Best Fit
4. Intuition of odds and log-odds
5. Feature selection using RFE
6. Model evaluation – Confusion Matrix and Accuracy
7. Why Accuracy is not Enough and introduction to sensitivity, specificity, precision, recall, area under curve
8. Logistic Regression Case Study
Day - 22: Unsupervised Learning:Clustering
Means Clustering:

1. Understanding clustering with practical examples
2. KMeans Clustering – understanding the algorithm
3. Practical consideration for KMeans Clustering – Elbow curve, silhouette metric and hopkings test for clustering tendency of data, impact of outliers

Day - 23: Unsupervised Learning
Hierarchical Clustering:

1. Hierarchical clustering Algorithm
2. Interpreting the dendogram and Types of Linkages
3. Comparison of Kmeans clustering and Hierarchical clustering – advantages and disadvantages

Day - 24: Unsupervised Learning:Principal Component Analysis(PCA)
1. Intuition behind PCA and practical examples
2. Variance as information and basis transformation of vectors
3. Singular Value Decomposition and Identifying optimum principal components using scree plots
4. Model building with PCA
5. Advantages of PCA and Limitations
Machine Learning - II
Day - 25: Support Vector Machine Algorithm
SVM:
1. Introduction to SVM and How does it works.
2. Advantages and Disadvantages of SVM
3. Kernal Functions in used in SVM
4. Applications of SVM
5. Implementation of SVM using Python
Day - 26: K Nearest Neighbors Algorithm
KNN:
1. Introduction to KNN and How does it works.
2. Advantages and Disadvantages of KNN
3. Applications of KNN
4. Implementation of KNN using Python
Day - 27: Naive Bayes Algorithm
Naive Bayes:
1. Intoduction to Naive Bayes
2. Advantage and Disadvantage of Naive Bayes
3. Applications of Naive Bayes
4. Implementation of Naive Bayes using Python
Day - 28: Tree Models
Decision Trees:

1. Introduction to decision trees and Interpretation
2. Homogeneity measures for splitting a node 1. Gini Index 2. Entropy 3. R2
3. Understanding Hyper parameters – Truncation and Pruning
4. Advantages and Disadvantages
Random Forest:

1. Introduction to ensembling, bagging and intuition
2. Random Forest – Introduction and Hyperparamters
3. Building a model using Random Forest
4. Hyper-parameters impact on model and tuning them
5. Importance of predictors using Random Forrest

Day - 29: Boosting
1. Intuition behind Boosting
2. Introduction to Boosting Algorithms : XGBoost, lightGBM, Catboost
3. Advantages of Boosting Algorithms
4.XGBoost Model Building and importance of various Hyper parameters
5. Hyper-parameter tuning for XGBoost
Day - 30: Case Study
Correlation and Regression Analysis of Physicochemical Parameters of River Water for the Evaluation of Percentage
Day - 31: Case Study
Telecom Churn – Group Case Study
Day - 32: Time Series
1. Introduction to Time Series
2. Trend and seasonality
3. Decomposition
4. moothing (moving average)
5. SES, Holt & Holt-Winter Model
Day - 33: Time Series
1. AutoRegression, Lag Series, ACF, PACF
2. IADF, Random walk and Auto Arima
Day - 34: Text Mining
1. Introduction to Text Mining
2. Text cleaning, regular expressions, Stemming, Lemmatization
3. Word cloud, Principal Component Analysis, Bigrams & Trigrams
4. Text classification, Document vectors, Text classification using Doc2vec
Day - 35: Case Study
sentiment analysis Twiter Data
Day - 36: Project Development
Day - 37: Project Development
Day - 38: Project Development
Day - 39: Project Development
Day - 40: Project Development
Day - 41: Project Development
Day - 42: Project Development
Day - 43: Project Development
Day - 44: Project Development
Day - 45: Project Development
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