syllubus

Let us have a look at them closely, as to what exactly you are supposed to learn in them

Mathematics and Statistics

Linear Algebra

Differential equations

Calculus

Multivariate and differential Calculus

Random Variables

Descriptive Statistics

Bayesian theorems

Probability theory

Optimization theory

Graph Theory, etc.

Programming languages

Python

R

Ruby

Perl

Java

Matlab

C, C++

Operating systems like Linux

Linux shell scripting

Databases

MySQL

Cassandra

MongoDB

You are also supposed to know of Analytics and Visualization since they are truly mandatory topics when you are planning to learn data sciences.

Thus, you would need more exposure to tools like Excel, Tableau, etc.

Again Machine Learning is an integral part of the subject which itself is a broader topic, which consists of many sub-topics like:

Regression (Linear, Logistic, Polynomial)

Decision trees

Boosted trees

Cross-Validation, actually many more!

Big data is another subset of Data sciences where you can specialize as well, which consists of topics like Hadoop, MapReduce, Spark, Apache, etc.

Another important part is the Deep learning segment, which consists of topics like Neural Networks, Hyperparameters optimization, YOLO, Object Detection, NLP or Natural Language Processing, computer Vision, etc.

Thus, you can clearly see that the topic is actually a vast one. And in order to become an expert in the same, you would highly need to be dedicated to learn the topic holistically.

However, note that, in this case, you are sure to require an expert hand to show you the right career path considering the vastness of the topic.

You need somebody to guide you completely and take you through all the topics one by one in a very streamlined manner, without confusing or intimidating you.

These days many institutes promise a complete syllabus with 100% placement assistance.

However you should stick to the ones that are genuinely interested in helping you out from scratch and also help you boost your confidence.

And therefore, I would highly recommend you attending the free online demo session conducted by the Digital Vidya Institute on their website to give you a proper gist of all these topics and help you with some more information on the subject.

What does a data scientist do?

“More generally, a data scientist is someone who knows how to extract meaning from and interpret data, which requires both tools and methods from statistics and machine learning, as well as being human. She spends a lot of time in the process of collecting, cleaning, and munging data, because data is never clean.

Is data science a good career?

Data Science is one of the most highly paid jobs. According to Glassdoor, Data Scientists make an average of $116,100 per year. This makes Data Science a highly lucrative career option

How can I become a data scientist?

How to Get a Data Science Job: A Ridiculously Specific Guide
Get on LinkedIn. Send twenty connection requests to data scientists. …
Get on GlassDoor. Read three data scientist job descriptions. …
Build a skill. Pick a skill and use it to build a small demo or tutorial. …
Interview. Only answer recruiters who know your name. …
Decline the offer.
Go to step one.

Is data science a stressful job?

Data scientists typically work on data for an entire company, which means scouring through thousands of transactions all at once. … “Data science is more exciting and adventurous than stressful,” he says. “It is only stressful when you are working to pay bills, and not to solve real-world problems,” he adds

Can freshers get job in data science?

Data science jobs are the talk of the town! A data science internship is one sure-fire way to understand the domain as well as to get a first-hand experience in this field. … Many final year graduate students look forward to a career in this new-age field.

About the course

The online course on data science offered by Crampete is a one-stop shop for all your data science learning needs. It offers you complete guidance and tutorial with downloadable resources and hands-on learning experience. The total duration of the course is 125 hours, and it can be attended from any location. There are over 200 videos and 100 quizzes to help you develop knowledge about the domain.

This course takes you through all the important modules that you need to know about, including machine learning and programming languages. It also teaches important concepts such as data acquisition, data mining, data processing, and data analysis.

This course is designed keeping in mind the current industry trends and skills required to become a successful data scientist. When you enroll for this course, you will receive one-to-one support from our instructors and practical-based learning experience. In this course, you will also receive complete support on how to go about job interviews and placements. Over 2000 students have benefited from our online data science course. Let’s see what some of our students have said about the course.

Introduction

The term data science was coined at the beginning of the 21st century, and it is a fairly young field of science and technology. Over the past few decades, data science has increasingly become popular all over the world. It has become the part and parcel of every business model. All forms of data run the world, be it personal data, website data, or behavioural data. With more and more number of Internet of Things being invented, we have shifted our focus to concepts like big data and data mining.

Companies have started to capitalize on big data, which controls the way people think and act. Data science has created a widespread impact across various sectors. In areas like healthcare, education, security, sports, energy, and science, the application of data science has created a lot of opportunities for innovation and improvement. Scientific studies rely on data sets to measure and anlalyze scientific goals, for example, healthcare recommendations, identifying and predicting diseases, personalized healthcare support via AI and machine learning, etc.

Data science syllabus offered by Crampete

Crampete’s data science syllabus includes a comprehensive curriculum, which is designed on the basis of what most industries want from data science professionals. The data science syllabus is suitable for beginners, working professionals, or someone who wants to switch over to a career in data science. There are six key modules [as mentioned earlier], which are further divided into nine lessons. These lessons cover a wide range of subjects – programming language, statistical tools, algorithms, and machine learning –

Module 1: Python
Python is the most important and necessary topic that every data scientist should have knowledge about. In this section, our instructors will take you through the basics of Python and areas where it can be used. You will learn how to use some of the current tools such as Numpy, Pandas, and Matplotlib. Therefore, modeule 1 includes –

Environment set-up
Jupyter overview
Python Numpy
Python Pandas
Python Matplotlib

Module 2: R
Used for statistical and data analysis, R programming language is one of the advanced statistical languages used in data science. This module teaches you how to explore data sets using R. Here you will learn –

An introduction to R
Data structures in R
Data visualization with R
Data analysis with R
Module 3: Statistics
When working with data, the knowledge of statistics is necessary and an imprtant skill set that you must have. In this module, you will learn –

Important statistical concepts used in data science
Difference between population and sample
Types of variables
Measures of central tendency
Measures of variability
Coefficient of variance
Skewness and Kurtosis

Module 4: Inferential statistics

Inferential statistics is used to make generalizations of populations, from which samples are drawn. This is a new branch of statistics, which helps you learn to analyze representative samples of large data sets. In this module, you will learn –

Normal distribution
Test hypotheses
Central limit theorem
Confidence interval
T-test
Type I and II errors
Student’s T distribution

Module 5: Regression and Anova

This lesson will help you understand how to establish a relationship between two or more objects. ANOVA or analysis of variance is used to analyze the differences among sample sets. Here you will learn –

Regression
ANOVA
R square
Correlation and causation
Module 6: Exploratory data analysis
In this lesson you will learn –

Data visualization
Missing value analysis
The correction matrix
Outlier detection analysis
Module 7: Supervised machine learning
This is a comprehensive module to help you understand how to make machines or computers interpret human language. You will learn –

Python Scikit tool
Neural networks
Support vector machine
Logistic and linear regression
Decision tee classifier
Module 8: Tableau
Tableau is a sophisticated business intelligence tool used for data visualization. In this lesson, you will learn –

Working with Tableau
Deep diving with data and connection
Creating charts
Mapping data in Tableau
Dashboards and stories
Module 9: Machine learning on cloud
In this lesson, you will learn –

ML on cloud platform
ML on AWS
ML on Microsoft Azure
Each of these lessons are taught by instructors who have years of experience and knowledge of data science and analytics. We guarantee you one-to-one mentoring, and also support you with assessments and interviews towards the end of the session

Data Science Skills you will master from this course
Besides data science skills, this course enables freshers and professionals to develop analytical and leadership skills. Additional skills that you will gain from this online course are –

Learn new programming languages
Learn to use frameworks based on tools like Hadoop and Apache Spark
Learn about NLP and neural networks
Gain hands-on experience on AI and machine learning tools
Know all about python and various forms of tools used in programming language, such Python Numpy and Pandas.
Learn how to use statistical models
Know about exploratory data analysis and learn to measure and analyze data sets using visual patterns.
Obtain one-to-one experience from instructors on supervised machine learning algorithms
Develop leadership skills and understand how to make business decisions
Understand data analytics and metrics important for any business
Improve communication ability and become more confident
Critical thinking and decision-making skills

Tools used to cover Data Science topics in our course
Data scientists require certain software tools for data operations. These tools are mostly statistical tools and programming languages used for data processing and analysis. Some of the tools used in Crampete’s data science course are –

Jupyter
Python Pandas
Python Numpy
Python Matplotlib
Statistical tools like T-test and ANOVA
SAS
Exploratoty data analysis tools like Apache Spark, Tableau, etc.
Excel
Machine learning tools
Python Ski-kit tool
Software to learn about neural networks and fuzzy logic
Matural Language Toolkit (NLTK), which are used by computers to interpret human languages.
Comparison of Crampete vs. other data science course syllabus
Crampete data science syllabus vs. IIT data science syllabus
If you want to study data science in India in any of the reputed institutions, then you can look for MS or M.Tech programmes offered by institutes such as IIT hyderabad, IIT Roorkee, and BITS Pilani. Most of these institutes offer admission based on merit and your work experience. Also, these institutes offer a minimum of 1-year programme; therefore, the course fee increases with the duration of programme that you choose to study. In addition to all this, some of these institutes have certain eligibility criteria, which makes it difficult for professionals and students from other different backgrounds to take up data science courses with these institutes. Also, the syllabus offered by these institutes is quite similar to what we offer on Crampete. Crampete focuses on essential topics like deep learning, Python, Apache Spark and other tools, and Big data. However, an IIT data science course might have additional topics because of the longer duration of programme, such as data structures and algorithms, computer organization, operating systems, machine learning tolls, and so on.

Crampete data science syllabus vs. MSc data science syllabus offered by various universities
If you wish to study masters in data science in any Indian universities and colleges, you will have to invest minimum 5 years. Other options open to you include diploma, integrated masters, bachelors, or certification courses in data science and analytics. Most of the private and public universities and colleges offering data science and data analytics masters courses have comprehensive syllabi, which include the following:

Knowledge of computer science and mathematics
Modelling and abstract thinking
Advanced theories
Software tools
Project management
Communication skills
In addition, most of the courses have certain eligibility criteria for admissions, and the course fee ranges anywhere between INR 1.7 and 3.5 LPA. [Did you know that institutes like Loyola College and Anna University in Chennai offer good quality courses in data science?]

Crampete data science syllabus vs. Udemy data science course syllabus
Udemy offers several intensive data science courses, such as deep learning, python, statistics, Tableau, data analytics, etc. Each of these modules are further divided into different sections with assessments. This means you have to pay for each of the sections that you want to study online. Udemy’s ‘complete data science bootcamp course’ gives you an introduction of various data science disciplines and their benefits, popular data science tools and techniques, and careers in data science.

Crampete data science syllabus vs. other online data science syllabus
If you are looking for advanced data science courses, you can check out Simplilearn’s data science course in collaboration with IBM. In this course you will learn to use necessary tools and gain an industry-recognized certificate. The course fee starts from INR 50,000. Likewise, other online learning platforms like UpGrad and Edureka, Intellipat offer simultaneous courses on data science and data analytics with masters and Pg diploma programmes. At UpGrad, you will find 12-month masters and Pg diploma programmes in data science in collaboration with the International Institute of Information Technology [IIIT] Bangalore.

What are the important areas in data science?
Data science is a vast field, and it offers a sea of opportunities for anyone who is interested to study. But, data science is not limited to the science of understanding the types of data available. There are several other components that you must understand if you want to be a data expert. The other equally challenging and important modules in data science include –

Data engineering
Big data engineering
Data analytics
Database management
Data mining
Machine learning or cognitive computing
Data visualization, and so on.
The above-mentioned subjects should be part of every data science lesson that you are looking forward to go through.

Data science with python syllabus
Python is the most commonly used programming language in data science. Data professionals all over the world must understand the fundamentals of Python and Python libraries to learn advanced data science and data analysis techniques. With Crampete, you can learn about Python fundamentals used in data science. Our course will help you jumpstart your career by providing you the required skillsets. Our data science with Python syllabus comprises environmental set-up and the core software tools used such as Jupyter, Numpy, Pandas, and Matplotlib.

What are the prerequisites for data science course?


There is no pre-defined eligibility to be a data scientist. People from various disciplines can choose data science as a career option. But, if you have qualifications like an engineering degree in computer science, electronics, or IT, it will be easy for you to understand many concepts that are part of the course. Also, a certification or degree in data science, data analytics, or AI always gives an edge over others who do not have either of it. On the other hand, a data science certification can also open up opportunity for many beginners in this field.

Duration and fee for data science course


The duration of the course depends on your pace of learning. Normally, most online data science courses last for 20 weeks. On Crampete, the total duration of the data science course is 125 hours. The course fee depends on the duration and medium of instruction. On average an online course on data science comes with a price tag of INR 20,000 and 50,000; the fee can increase based on the provider and duration of study. Crampete’s data science course will cost you just INR 25,000.

Recommended institutes to study data science


Crampete is the best place to learn Data Science. But for some reasons if you are looking for other institutes to study online data science courses, you can look into the following. Coursera, Simplilearn, Edureka, and Intellipat. Many private and public colleges have shifted to the online medium of delivering courses.

Therefore, you must keep an eye on your nearest institutes offering full-time and weekend online data science programmes. Want to know if the Data Science career is suitable for you? Want to know our placement assistance and data science course details? call us at +91 93840 58984 and talk to our data science course manager.

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