Summer Internship 2023

  • Summer Internship 2023

COMPLETE TRAINING ON TECHNOLOGY | PROJECT DEVELOPEMENT


Training Fee

Rs.6500 /-

May June July

Register Now

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 2023

Hey there student, how are you? Have you started your Summer Internship 2023 yet, or are you still looking for a decent programme? You don’t have to be concerned because TruProjects will provide you with the greatest Student Internship Opportunities 2023. For our Summer Internship Program 2023, we take pride in delivering the greatest supervision and training, which you can access at any time. If you’re looking for an Online Summer Internship Institute 2023, you’ve come to the right place. If you are a student or a graduate, Tru Projects’ Online Summer Internship Program 2023 is unquestionably the best option for you. You will undoubtedly receive domain expertise and job experience by participating in the Student Summer Internship 2023. Because it has been established that students who participate in internships develop a lot of practical skills, we recommend that you apply for our Summer Internship for Students 2023. We believe that the Summer Internship Training 2023 will assist you in developing vital skills and keeping you current with the latest technological foundations.

We also offer IT Summer Internship 2023, a programme geared toward students interested in the field of information technology. This training will most likely provide them with high-quality resources as well as mentorship from knowledgeable faculty. Interning will always benefit us while applying for full-time jobs or pursuing a higher degree in any sector. Are you aware that TruProjects has Summer Internship Openings for 2023? That’s correct. Every year, we hire interns to assist them in gaining experience in various industries. As a result, by participating in the Online Summer Internship 2023, you will have the opportunity to collaborate with fresh students, share your knowledge, and improve your teamwork abilities. Tru Projects’ online Summer Internship with Certificate 2023 will be facilitated by highly qualified instructors with years of expertise in the area. TruProjects also provides a Software Engineering Summer Internship 2023 that focuses on the foundations and fundamentals of software engineering. You can also participate in our Virtual Summer Internship 2023, which allows you to work as an intern from the comfort of your own home without having to travel.

You will find internships  for final-year students 2023, who can come work for us as interns during their senior year of college. Without a doubt, participating in the Summer Final Year Internship 2023 will provide several benefits, including learning how to perform current projects and what software is used. So don’t wait any longer and sign up for one of TruProjects’ Final Year Summer Internships in 2023. As far as possible, we want to provide Student Internship Opportunities 2023. This is because we recognise the value of working before beginning a career. Including our 2023 Internship Program in your daily routine will undoubtedly benefit you both intellectually and practically. If you’re seeking for an Internship Training Program in 2023, go no further since we’re the Best Internship Training Institute in 2023. The most significant advantage of the Internship certificate Training 2023 is that you will be instructed and certified by highly qualified specialists. The Software Development Internship 2023 and the Software Engineering Internship 2023 are also available through Tru Projects. You’ll learn about the industry of software engineering and development, including how software is built and tested for mistakes or flaws, as well as how the model can be further evolved for public distribution.

Isnt it hard to pick proper internships for Freshers 2023?. We’ve all been in a situation in college where we feel our skillset isn’t quite up to par and want to improve. By participating in our Online Internship Training Program 2023, you will get a head start on your peers. The reason for this is that our online Internship for engineering students in 2023 does not demand you to sacrifice your personal time. As a result, you can work as an intern online and manage your schedule accordingly. Are you interested in becoming a software engineer intern or a software development engineer intern in 2023? With our meticulously crafted Software Development Engineer Internship 2023, we’ve got you covered. This is mostly intended for people who want to learn more about how software industries operate. Some of us also want to take our time learning about the subject of technology and the various divisions within it. We provide the Best long-term Internship Training in 2023, which enables you to accomplish so. This Long Term Internship Training 2023 will provide you with the opportunity to learn for a longer length of time with no restrictions. In addition, by participating in the Long Term Internship Program 2023, you will have the opportunity to work directly with the mentors and contact with them on a daily basis as needed. The Tru Projects Professional Internship 2023 is designed for recent graduates or working professionals who want to obtain further work experience in the field. The paid Internship for engineering students 2023 is a popular one at Tru Projects. The Full Time Paid Summer Internship 2023 allows you to make money while learning and working at the same time.

The real-time summer internship 2023 at TruProjects allows students to put current trending projects into practise under the supervision of experts. On the real-time summer internship programme 2023, the trainers will assign students work, explain crucial topics, and keep a careful eye on them. How frequently do you come across Online Internships for students in 2023, let alone a Full-Time Summer Internship Program in 2023? Tru Projects’ Summer College Student Internship 2023 assists you in achieving your professional goals at your own pace. We also have a Long Term Internship Opportunity 2023 that is usually a component of or an extension of our Summer Internship Training Course 2023. Let us assure you that the Online Summer Internship Training 2023 will undoubtedly assist you in learning more than what we were taught in college through books. You will most likely be ahead of the game when it comes to job interviews if you participate in one of our Programming Internships 2023. Our students can also participate in the Software Engineering Internship Program 2023. Numerous people are aware that our Software Engineering Internship 2023 has assisted many engineers in obtaining positions at reputable businesses. After working as a Software Engineer Summer Intern 2023 at TruProjects, you’re likely to become a lot more analytical. Our organisation offers internships such as the Internship Program For Graduates 2023 and the Internship Program For Freshers 2023. Summer Analyst Internship 2023 is one of Tru Projects’ unique summer internships for undergraduates in 2023. Data analytics has recently become a popular topic in technology, and this internship will teach you the fundamentals. Another distinguishing feature is the Summer Research Internship 2023.

Many students want to learn about many aspects of technology and want to do so in a comfortable environment. Our Summer Research Internship Program 2023 will enable you to pursue your research ambitions while also preparing you for future success.

If you want to be both a researcher and a creator, the research Internships for Undergraduates 2023 is the appropriate programme for you. The Engineering Internship Program 2023 is an excellent choice for engineering students since it will allow them to understand the fundamentals in a hands-on environment before moving on to more advanced levels of concepts, making future endeavours easier. Summer Technical Internship Program 2023 is primarily conducted by Tru Projects in order to assist students in updating their technical abilities to a more intermediate level.

So, if you think you need to brush up on your tech skills, this is the one for you. If you’re looking for Paid Programming Summer Internship 2023, you should contact us as soon as possible. Our Programming Intern Undergraduates 2023 programme is specifically designed for individuals who want to improve their programming skills. You can also earn money by participating in the Paid Programming Summer Intern 2023. The Certification Internship Undergraduates 2023 will provide you with the opportunity to work with highly qualified mentors and will also provide you with a certificate at the conclusion of the internship. Paid Certification Summer Internship 2023 or Paid Summer Intern Programme 2023 is a fantastic way to spend your summer vacation. You will be acquiring new abilities that will benefit you in a variety of ways. Without a doubt, the Paid Summer Internship Programme 2023 will be beneficial to you.  Feel free to take a look at our other choices, such as Intern Programme b tech Students 2023 and Tru Projects’ Intern Programme Undergraduates 2023, which are designed to assist students in a variety of ways. Learning, we believe, can be enjoyable and not taxing. Please contact us for more information on our Computer Science Internships 2023 or the various sorts of internships that are available.

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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