To join our Data science classroom course in Delhi or offline course, the minimum duration of the course is three months, you can also take it forward to 6 months and then finally a diploma of 1 year. Once you choose the course of any duration, you can exceed it as per your choice and preference if you feel there is a need for you to learn more about the course. As the duration of the course increases, so do the modules differ providing more in-depth knowledge about Data Science Course.

The answer to your question is Yes. We do offer certifications post the completion of your entire course. Our certificates are authorized and well-recognized and are ISO certified which can be acknowledged anywhere you go, to provide you with a unique achievement that you must have been longing for. Our Data Science course in Delhi NCR consists of a minimum of 3 Months of course where you will only be given a ‘completion of course certificate’ and if you are opting for 6 Months or 1 Year, of course, you will get an internship letter direct from the company’s name- Orangus Digital which will benefit you in your future. Whereas, on the other hand, you will also achieve a certificate of completion, be it any course you opt for.

Our trainers at Techstack have a wide experience of over 8+ years, who have worked in the most well-renowned tech companies. They lay equal emphasis on providing you with the group as well as one-on-one training if required. Get practical data science training in Delhi with our professionals and enhance your already existing skills! They will also help you out with your CV and improve your chances of success by demonstrating your skills efficiently and clearly, to help you get through in your career and make a venture in the field that you have chosen for your future endeavors. Out trainers assure greater responsibility whilst grooming them for leadership positions.

Yes. At Techstack Academy, our trainers are readily available to clear your doubts whenever required. You can also avail of online classes or go through the recorded sessions available, which can give you a clearer understanding of the course. If you are lagging somewhere or haven't understood any topic, you can reach out to our trainers, anytime. It is mandatory to first ask for the trainer’s time and availability before you think of clearing your doubts thoroughly.

Anybody can apply for the course at Techstack Academy. There is no certain minimum age or a maximum age limit to enroll for a Data Science course in Delhi. We train students of all age groups irrespective of whether you are senior school passed, graduate, or are a little aged. Learning has no age limit. Our Academy focuses on providing education to every individual who comes in to seek knowledge from us. With a foundational and recognized certificate provided by us, you will get the same educational benefits as learning in any college.
We provide them with the utmost knowledge, with an exclusively designed curriculum that would suit them best with their preferences.

Since everything is running digitally nowadays, we intend to offer our students the best of knowledge in both online and offline terms. If you are not comfortable in attending offline classes, you can easily avail Data Science online course at Techstack Academy where we provide you with immense knowledge whether it’s online or offline. The only difference to choose online classes would be that the amount of fee would slightly differ in comparison to the offline lectures taken. Depending on the course you choose, the online classes will be based and provided on those particular hours to the particular batch of students.

If you are willing to avail the best data science course in Delhi, joining Techstack Academy will surely provide you with demo/ trial classes for students. Just make sure that you select the subject and time of the class beforehand so that you get an independent assessment to avail the quality of teaching at our institute. We provide online as well as offline demo sessions, you can choose any as per your convenience. This will help and ensure you why to join Techstack Academy in order to build your career better in the field of Data Science.

Yes, of course. The internship programs are included in the course chosen for more than 3 months of duration wherein a student can learn, grow and lay hands on the practical information of the data science course. We are regarded as the best institute for Data Science in Delhi, providing our students with an internship of nearly 45 days, if you opt for the course of 6 months, this will also include the internship letter issued for them so that it can be beneficial for them in their future purposes. If you are willing to go for a 1-year course, you will have a paid internship of 6 months. There is no internship available in the course duration of 3 months.

Yes, of course. The internship programs are included in the course chosen for more than 3 months of duration wherein a student can learn, grow and lay hands on the practical information of the data science course. We are regarded as the best institute for Data Science in Delhi, providing our students with an internship of nearly 45 days, if you opt for the course of 6 months, this will also include the internship letter issued for them so that it can be beneficial for them in their future purposes. If you are willing to go for a 1-year course, you will have a paid internship of 6 months. There is no internship available in the course duration of 3 months.

We, at Techstack, provide a vast array of knowledge to our students by focusing on both, lecture as well as discussion-based training. We believe, having both from time to time on a regular basis helps the students to grow and learn better. This will also enable the students to portray their opinions and ideas during the discussion-based session, which will help the trainer as well as the student to have a great interactive session. To learn more, achieve better, and reach great heights, our both sessions are considered essential and worthy, as we have received various positive feedback regarding the same. Join our data science course now, and diversify your knowledge.

Data science is regarded as an interdisciplinary field that moves forward with the scientific methods to extract algorithms, systems processes, and insights from the structure and/or unstructured data. The importance of data and our capability to analyze, consolidate, and contextualize it relies upon the data scientists to fill this need, but there is a serious lack of qualified candidates worldwide.

If you're moving down the path to becoming a Data Scientist, then choose the best data Science course in Delhi, that serves you with immense knowledge starting from the basics to helping you transform into an expert. Make your career in the field of Data Science. Examine which questions need answering and where to find the related and relevant data, only by joining Techstack! Enhance your tech skills with us!

There is a lot of difference between supervised and unsupervised learning. You will understand many aspects about it, once you join our Data Science course.

Supervised learning majorly focuses on learning the algorithms that are labeled dataset, and provides an answer key to evaluate the algorithm which is used to evaluate its accuracy on training data. An unsupervised model is referred to as the learning that provides unlabeled data and contains a certain algorithm that tries to make sense by extracting features and patterns on its own. Both the learnings have different techniques and strategies to be followed for maintaining and having to enable the user to specify an algorithm to use the desired number of output classes.

Logistic regression is used to estimate the log odds of an event. The regression is mostly used for binary classification, which is considered for predictions of the type this or that, yes or no, A or B, etc. Logistic regression is also used for multiclass classification, but it is also used in the simplest applications. You can break the assumptions into various segments, namely- Binary output value, removal of noise, gaussian distribution, removing correlated inputs, and so on. Joining Techstack, you will be first introduced to the overview of Logistic Regression and soon will discover the entire topic in-depth regarding the data science course syllabus with our experts of Data Science.

Both the subjects are included in our machine learning course wherein you will be given knowledge about the difference between Regression and Classification algorithms that are known in Supervised Learning algorithms. The major difference between the two states is that they are used to predict the continuous values such as salary, price, age, etc. whereas the classification algorithms are used to predict and classify the discrete values such as Male or Female, True or False, Spam or Not Spam, etc.

Various type of ML classification:

Logistic Regression

• K-Nearest Neighbour
• Support Vector Machines
• Naïve Bayes
• Kernel SVM
• Decision Tree Classification
• Random Forest Classification

Types of Regression Algorithm:

• Simple Linear Regression
• Decision Tree Regression
• Polynomial Regression
• Multiple Linear Regression
• Support Vector Regression
• Random Forest Regression

Ensemble learning is one of the most powerful modules of our Data Science course, inhibiting work in a manner that can foster and improve the performance of your module. The ensemble learning includes various sub-topics when taught by our experts, this may involve checking for the difference in population, difference in modeling techniques, varied hypotheses and with the difference in the initial seed etc. There are various components that are used to bifurcate and rectify any kind of error that arises within ensemble learning. The errors are provided with a proper insight, boosting the iterative techniques to increase the weight of any observation and the vice-versa.

Data cleaning can help in analyzing better performance because cleaning the data from multiple sources helps to transform the data into such a format wherein the data analyst and scientist finds it easy to work with. This also enables to increase the accuracy of the model into the segment of machine learning. Once the cumbersome process is activated, the number of data sources increases exponentially with the time taken to clean the data generated by such sources. This might take upto 80% of the time to clean the data thereby making it a critical part of the analysis task.

This is another powerful module when it comes to joining our data science course in Delhi. Decision trees work in a manner which is a tool used for classification, and prediction. This is like a flowchart which is a tree structure wherein each internal node denoting a test on any attribute. Particularly every branch provides a representation, with an outcome of the test with every leaf node holding up with a class label. The representation of the decision tree classifies by sorting the issues down handling with some high dimensional data. In general, the decision tree induction is a typical inductive approach to learn knowledge on classification.

Deep learning is a broader term in the field of Machine Learning, which uses Artificial Neural Networks (ANN) in order to derive top level features from the input. Deep learning is the sub-branch of Machine Learning. A deep learning framework allows researchers and developers to attain the state-of-art compactly, efficiently and robustly. This helps in enabling the training and testing of models using APIs. These also provide high-level performance and better management of dependencies to segment different frameworks. Different kinds of deep learning frameworks include Tensorflow, Caffe, Pytorch, MXnet and many more. They have a tendency to match (and even exceed) the cognitive powers of the human brain.

Maintaining a deployment requires certain skills as you must integrate a machine learning model into an existing production environment to make practical business decisions based on a particular data. People often have a misconception that maintaining a deployed model may take forever, which is not true as all you need to do is to maintain your models like you maintain a machine. Machine Learning models can get off or broken with time which sounds a little because they have no moving pieces. But to adapt strategies for this, you might be needing a change and drifts of concept part clear. Drift concept can easily approach the concept by making the window moving over time and you can thus catch drifts of concepts. This will also help by reducing issues with drifts of concepts.

Machine Learning is considered to be the most intense algorithm field in computer science. Python machine learning libraries have grown to the most which has now become the most preferred language for algorithm implementation. There are plenty of machine learning libraries that are used, namely- SciPy, NumPy, Theano, Pandas, Scikit-learn and many more. Python is considered as the top go-to language when it comes to choosing a data science course for your career. The above mentioned common libraries is a group of an active community that most developers create for their personal purposes and later release it to the public for their benefit.