Summer Internship 2022

  • Summer Internship 2022

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 2022

Hello there reader. Have you begun your Summer Internship 2022 or are you yet to enroll yourself into a good institute? You need not worry much as you can find the best Student Internship Opportunities 2022 at TruProjects.We take pride in providing the best guidance and training for our Summer Internship Programme 2022, which you can also have access to any time now. If you are on the hunt for an Online Summer Internship Institute 2022, you need not search further as you can find your requirements at one single place. The Online Summer Internship Program 2022 at Tru Projects is surely the right choice for you if you are a student or a graduate. Undoubtedly by doing the Student Summer Internship 2022, you will be able to gain industry level knowledge and work experience. It is proven that by doing internships, students tend to learn many things practically hence we advise you to choose our Summer Internship for Students 2022. We believe that the Summer Internship Training 2022 will help you equip yourself with necessary skills and keep you up to date with the latest foundations of technology.

We also provide IT Summer Internship 2022, which is specifically targeted towards students in the Information Technology sector. This training is likely to provide them quality resources and mentorship from trained faculty. Being an intern is always going to help us when we apply for full time job roles or wish to pursue a higher degree in any field. Do you know that TruProjects also has Summer Intern Openings 2022? Yes it does. We hire interns every year to help them gain knowledge about the industries as a whole. So by doing the Online Summer Internship 2022, you can also be able to work with new students and share your knowledge and hone your team work skills as well. The online Summer Internship with certificate 2022 at Tru Projects will be hosted by trained faculty who have years of experience in the field. TruProjects also offers Software Engineering Summer Internship 2022 which majorly targets the foundations of software engineering and the fundamentals of it. You can also attend our Virtual Summer Internship 2022, which allows you to be an intern from your own home without the need of travelling from one place to another.

There is also an Internship for final year students 2022, who can come and work for us as interns when they are in their last year in college. Undeniably, by being a part of the Summer Final Year Internship 2022, one can gain numerous advantages such as learning how the latest projects are executed and what softwares are used. So do not wait further and enroll yourself into our Final Year Summer internships 2022 at TruProjects. We are aiming at providing Student Internship Opportunities 2022 as much as we can. This is because we understand the importance of working prior to entering the professional world. By including our Internship Program 2022 in your daily routine will definitely help you theoretically and practically. If you are currently looking for Internship Training Program 2022 then you need not search further as we are the Best Internship Training Institute 2022. The biggest benefit of the Internship certificate Training 2022 is that you will be trained and certified by experienced professionals. Tru Projects also offers the Software Development Internship 2022 and the Software Engineering Internship 2022. You will gain exposure about the field of software engineering and development, as to how a software is first created and monitored for errors or bugs and how the model is further developed for distribution in the market.

We also provide Internship for Freshers 2022. All of us have been stuck at a point in college where we feel that our skillset is not up to the point and want to get better. You will have a jumpstart than your colleagues by doing our Online Internship Training Program 2022. The reason is that our online Internship for engineering students 2022 doesn’t require you to compromise on your fun time. Which means you can plan your schedule accordingly and then work as an intern online. Are you looking forward to be a Software engineer intern 2022 or a Software Development Engineer Intern 2022? We have got you covered with our carefully designed Software Development Engineer Internship 2022. This is mainly aimed towards individuals who wish to understand how the industries which create softwares work. Also, some of us wish to explore the field and different departments in technology at our own pace. We offer the Best long term Internship Training 2022, thus allowing you to do so. This Long Term Internship Training 2022 will give you the benefit of learning for a longer period of time with no limitations or constraints. Also by doing the Long Term Internship Program 2022, you get to closely work with the mentors and interact with them on a daily basis whenever needed. The Professional Internship 2022 at Tru Projects is meant for graduates or for working professionals who wish to further gain some work experience in a new domain. A very popular one at Tru Projects is the paid Internship for engineering students 2022. The Full Time Paid Summer Internship 2022 will let you earn money and also learn and work in parallel.

The real time summer Internship 2022 at TruProjects lets the students implement the current trending projects practically with the guidance of the faculty. The trainers on the real time summer Internship program 2022 will assign students their work, explain the key concepts and monitor them closely. How often do you find Online Internships for students 2022 let alone Full Time Summer Internship Program 2022? Our Summer College Student Internship 2022 at Tru Projects helps you achieve your professional goals at your own convenience. We also offer the Long Term Internship Opportunity 2022 which usually is a part or extension of our Summer Internship Training Course 2022 course. Let us tell you that the Online Summer Internship Training 2022 is surely to help you learn more than what all of us are taught in colleges from books. By doing any of our Programming Internships 2022, you are likely to be ahead of the game when it comes down to job interviews. We also provide the Software Engineering Internship Program 2022 for our students.

It is known to many that our Software Engineering Internship 2022 has helped so many engineers land jobs at reputed companies. You are likely to be a lot more analytical after being a Software Engineer Summer Intern 2022 at TruProjects. The Internship Program For Graduate 2022 and the Internship Program For Fresher 2022 are some of the internships you often find in our company. One of the unique summer Internship for undergraduate 2022 at Tru Projects is the Summer Analyst Internship 2022. Data analytics has lately been the trending field in technology and this internship will help you begin from the basics. The Summer Research Internship 2022 is also another unique factor. Many students wish to explore the diverse areas in technology and prefer to do it in a slow paced environment. Our Summer Research Internship Program 2022 will allow you to pursue your research oriented goals and help you excel in the future.

Therefore if you wish to be a researcher or a developer too, the research Internships for undergraduates 2022 is the right choice for you. The Engineering Internship Program 2022 is a great choice for students from the engineering fields as it will help them learn basics in a practical manner and then move on to advanced levels of concepts, thus making it easier during future endeavours. Tru Projects majorly conducts the Summer Technical Internship Program 2022 in order to help students with upgrading their technical skills in a more intermediate level. So if you believe you need to develop your tech knowledge, this one’s for you. If you are on the hunt for Paid Programming Summer Internship 2022, then you need to reach out to us soon. As our Programming Intern Undergraduates 2022 is purely created for students who wish to develop their programming skills.You can also be a part of the Paid Programming Summer Intern 2022 and earn money as well.

The Certification Internship Undergraduates 2022 will let you work with highly skilled mentors and also give a certificate at the end of the internship. The Paid Certification Summer Internship 2022 or even the Paid Summer Intern Programme 2022 is truly a great chance for you to spend your holidays. You will be learning new skills which might help you in many ways. Undoubtedly, you will benefit from the Paid Summer Internship Programme 2022. You can also look at our other options such as Intern Programme b tech Students 2022 and Tru Projects provides the Intern Programme Undergraduates 2022 with the main purpose to help students in many ways possible. We believe learning can be fun and not strenuous. Therefore please contact us for further details about our Computer Science Internships 2022 or also the different types of internships 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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