Data Science Course = Excellent career choice
Data science is a new and popular profession with several employment options for recent grads.
Data science is a branch of computer science that combines programming, statistics, and business intelligence with subjects such as machine learning, artificial intelligence, and business analytics to extract useful information from massive volumes of data.
Data scientists are in great demand because they can apply their abilities in various industries, including healthcare, finance, retail, education, and many more. The need for data scientists has increased by 31% each year over the previous decade. In India, their typical compensation ranges from 6 to 10 lacs per year, depending on location and company size.
If you have robust Data Science abilities, you may acquire jobs such as Data Analyst, Business Intelligence Analyst, Data Visualizer, and so on.
Data science is one of the top five jobs that young people globally wish to study, and it will only grow in popularity in the coming years.
1. Trainers with Industry experience
All our instructors have real-time experience working in reputable organizations and a thorough knowledge of the Data Science domain.
2. Limited batch size
We limit our Online Data Science course to 6 students every batch so that we can give individual attention to each one.
3. Frills-free syllabus
Unlike other institutes that attempt to attract students with fancy terminology and unnecessary topics, we only teach what a student needs to know to enter the Data Science field.
4. Projects-based training (SOAP)
We provide our online Data science course students a lot of tasks and assignments using a SOAP system (Student Output Assessment Plan) and give them valuable feedback.
5. Lively & Interactive classes
Because our batch sizes are small, the classes will be highly interactive; with our data science course, students are encouraged to ask any number of questions during the session.
6. Recorded sessions
All sessions would be recorded and shared with students so they could watch and learn from them afterward.
7. Placement support
We have a professional placement team that assists all our students in their placement journey, from resume creation to finding a good job.
Years of Excellence
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Our Course Syllabus offers additional topics for the students' advantage.
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Few things to know before joining our Data science online training program
Data science is an umbrella term that incorporates, among other things, data analytics, data mining, and machine learning. A data scientist is an expert who captures, analyses, and interprets massive amounts of data. Data scientists often deal with uncertainty by predicting the future using advanced data tools.
Data Analytics is a subset of Data Science. A data analyst uses data to discover critical insights about a company's consumers and to devise problem-solving methods. Data analysts frequently employ structured information to address actual business issues by utilizing technologies such as SQL, R, or Python programming languages, data visualization applications, and statistical analysis.
A subfield of data science is data visualization. The pictorial depiction of data and information is known as data visualization. Data visualization tools use visual components such as charts, graphs, and maps to make it simple to identify and comprehend trends, outliers, and patterns in data. Tableau, Power BI, and Excel are three of the most popular data visualization tools.
Python is an essential tool in the data analyst's toolbox because it is well-suited for conducting repeated operations and data manipulation, and anybody who has worked with large amounts of data understands how frequently repetition occurs. Once you've grasped the foundations of Python, you should look into libraries like NumPy, Pandas, and Matplotlib, which aid the data analyst in carrying out their obligations. Tensorflow, Keras, and Theano are just a few of the Python packages that may assist data scientists in developing deep learning algorithms.
Math and statistics are essential for Data Science since they are the foundation for all machine learning algorithms. Data scientists use statistics to collect, assess, analyze, and derive conclusions from data and apply appropriate quantitative mathematical models and variables. The use of linear algebra enables the efficient completion of various critical computations.
Machine learning examines and assesses enormous volumes of data automatically. It automates data processing and delivers predictions in real-time without the need for human interaction. A Data Model is created automatically and then trained to produce real-time predictions.
SQL (Structured Query Language) is a computer language used in relational databases to query and manage data. SQL performs a variety of actions on database-stored data, such as updating and deleting entries, creating and modifying tables and views, and so on.
Deep learning is an essential part of data science, along with statistics and predictive modeling. Deep learning is a subset of machine learning that allows a computer to do human-like tasks such as speech recognition, image identification, and prediction. It increases the ability to classify, identify, detect, and define data-driven objects.
The core objective of Artificial Intelligence is to use computers to replicate human intelligence so that machines can make intelligent decisions in difficult situations. Machine Learning is a Supervised type of Artificial Intelligence and Data Science together, whereas Artificial Intelligence is a tool for Data Science.
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Data science has enormous potential in every industry in India, from banking and cyber security to education, healthcare, and even small companies. Because data science is a popular job option with great pay, you must have a high degree of education and excellent competence.
College graduation with strong communication and analytical skills is required. A thorough understanding of mathematical concepts is one of the essential Data Science qualifications.
The annual salary of an entry-level Data Scientist can range from 3L to 10L, depending on the student's abilities and the company's compensation structure.
We question students who wish to take a Data science course to find out what drives them to pursue a career in this field. Math is essential to Data Science, so we expect the student to be proficient in it. A background in technical education and strong communication skills are also required.
We have taught students for almost seven years and trained over 2,500 people. Our trainers have all had at least five years of experience in the field. We have a 100% placement record. As part of the SOAP (Student Output Assessment Plan) teaching system, we assign several academic tasks to our students.
Please get in touch with our academic counselor at 9791333350 to enquire about fees. We do not offer refunds since the number of students in a batch is limited, and it would be unfeasible to allow a student to drop out of such a small batch.
All our sessions (both online and in-person classes) are recorded, and you will receive a recording of each session to help you learn or revise.
Our data science tutors have at least five years of industry experience. Their real-time project experience would benefit their students since they could impart more in-depth knowledge. All our Data science instructors are friendly with their students and help them as much as they need till the course is completed.
We only provide demo classes to students who wish to enroll in online courses. The demo classes will last between 30 and 45 minutes.
We create tasks similar to real-time projects to provide our Data science students with the same professional experience. Students who train with our trainers will learn a lot because they have real-time expertise.
We provide 100% placement assistance but make no assurances about placement. Promising placements is hard because they depend on students' discipline and abilities.
I genuinely loved the data science course offered here. The course was very helpful for someone like myself who wanted to transition to data science from a non-IT domain. The syllabus was well-tailored and covered everything from basic all the way till advanced topics.
