Highlights of Our Data Science Course in Chennai
Data science is a multidisciplinary field that uses techniques, tools, algorithms, systems to extract knowledge, actionable insights from data and apply knowledge to solve problems across a broad range of application domains. Digitalization is the key to the success of the business, which makes data science the most promising field in IT. Let’s see the highlights of Our Data Science Course in Chennai and transform it to the next level.
First and foremost we ensure providing in-depth knowledge to our aspirants by taking our data science course in Chennai to the next level with the help of syllabus and training by our team of data science engineers who are industry experts in this field.
We understand our aspirants which make us provide the best training in terms of course type, timing, doubt clearance, assessment, projects, personalized attention.
Most importantly, our best data science course in Chennai training leads you to grab your dream job with the help of our dedicated placement cell. Our job assistance involves professional resume building, mock interview, job reference, interview scheduling.
Course Features
- Duration80 to 100 Hrs
- Skill levelAll level
- Batch Strength15
- AssessmentsYes
- Mock InterviewsYes
- Resume BuildingYes
- PlacementsYes
- Flexible TimingYes
- Fee InstallmentsYes
- LanguageTamil/English
CHAPTER 1: Introduction to Data Science
- Market trend of Data Science
- Opportunities for Data Science
- What is the need for Data Scientists
- What is Data science
- Data Science Venn Diagram
- Data Science Use cases
- Knowing the roles of a Data Science practitioner
- Data Science – Skills set
- Understanding the concepts & definitions of:
- Artificial Intelligence
- Machine Learning- Deep Learning
- NLP
- Computer Vision
CHAPTER 2: Data and Tools
- What is Business Intelligence?
- What is ETL?
- Layers of a Data Warehouse
- OLAP VS OLTP
- Facts and Dimensions
- Big Data tools and it’s uses
- Big Data stack
- Understanding Structured text Data
- Understanding Unstructured text Data
CHAPTER 3: Data Science- Deep dive
- Understanding Descriptive vs Predictive vs Prescriptive Analytics
- Difference between Analytics vs. Analysis
- Data Science Project Lifecycle
- Technology Stack Involved in the Lifecycle
- Machine Learning tools
- Development tools
- Languages
- Data Platforms
- CRISP - Cross-industry standard process for Data Mining
- 5WIH- The questions that kick start a ML project
- 80-20 Rule of Data Analytics
- Supervised Vs Unsupervised Learning
- Data Science- Use case bubble
- Data Mining techniques
CHAPTER 4: Data
- Data Wrangling or Data Munging
- Data Categorization basics
- Different Types of Data
- Types of Data Collection
- Data Sources
- Data Collection plan
- Data Quality Issues
- Types of Data Error
- Ration Scale Vs Interval Scale
- Predictors/Features vs Predictions/Labels
- Understanding Imbalance in Data
CHAPTER 5: Statistics & Probability
- What is Statistics
- Sample Vs Population
- Measure of Central vs Dispersion
- Frequency Distribution
- Cumulative Frequency Distribution
- Mean, Median, Mode
- Quartiles/Percentile
- Range, Variance, Standard Deviation, Co-efficient of Variation
- 68-95-99 Rule of SD
- Z Score (Standard Score)
- P-Value
- Maximum Likelihood Estimation
- Probability vs Likelihood
- PDF vs PMF
- Normal Distribution of Data
- Skewness & it’s types
- Kurtosis & it’s types
- Kth Central Moments
- Co-Variance/Joint Probability Distribution
- Correlation
- Entropy
- ANOVA
- Chi-Square
- F tests
- Types of Data Distribution
Real-time Practicals
- Hands on- Lab using pen and paper Only
CHAPTER 6: Setup
- Anaconda & Python
- Understanding Jupyter Notebooks
- Python Package Installation
- Tableau Installation
- Oracle Database & Server
CHAPTER 7: Data Sourcing, Exploratory Data Analysis & Readiness
- Concept of List, Data frame, Dictionary
- Connecting to Databases using Python
- Importing data from csv, text, Excel
- Converting JSON, XML, to Data frame
- Understanding EDA
- Frequency Distribution
- Analyzing NA, blanks
- Using SQL concepts inside Python
Real-time Practicals
- Hands on- Lab using Python
CHAPTER 8: Data Transformation/Wrangling
- Handling missing Values
- Handling Outliers
- Normalization techniques
- Standardization techniques
- Regularization techniques
- Feature Extraction
- Train Test data selection
Real-time Practicals
- Hands on- Lab using Python
CHAPTER 9: Data Science Concepts
- No Free Lunch
- Hypothesis vs Null Hypothesis
- BIAS VS Variance tradeoff
- Local Vs Global Minima/Maxima
- Bias – Loss/ Loss-Cost Function
CHAPTER 10: Linear Regression
- Understanding Regression math
- Linear Algebra concepts
- Least Mean Square
- Analyzing Co-relation
- Heat Maps, Pair Plots, Distribution Graphs
- Simple Vs Multiple Linear regression
- Train Test data selection
Real-time Practicals
- Hands on- Lab & Model Implementation using Python
CHAPTER 11: Polynomial Regression
- Understanding the math
- Polynomial Algebra concepts
- Degree of Polynomial
Real-time Practicals
- Hands on- Lab & Model Implementation using Python
CHAPTER 12: Classification
- Overfitting/ Under fitting/ Optimal Fits
- Handling Categorical Data inside
- Confusion Matrix
- Type I & Type II errors
- Precision Vs Accuracy
- AUC/ROC curve
CHAPTER 13: Logistic Regression
- Understanding the statistics behind Logistic Sigmoid
- Logistic regression math
Real-time Practicals
- Hands on- Lab & Model Implementation using Python
CHAPTER 14: Random Forest
- Understanding the Decision Tree & Bagging
- Math behind Classification and Regression in tree
- Decision Tree concepts
- Using Random Forest for Regression
- K fold Cross Validation
- Model Optimizers
- Hyper parameter Tuning
Real-time Practicals
- Hands on- Lab & Model Implementation using Python
CHAPTER 15: Naïve Bayes Theorem
- Understanding the Naïve Bayes theorem
- Bayesian Vs Gaussian theorems
- Using naïve Bayes for Regression
- Model Optimizers
- Hyper parameter Tuning
Real-time Practicals
- Hands on- Lab & Model Implementation using Python
CHAPTER 16: NLP for Machine Learning Featuring
- Label Encoding
- One hot encoding
- Synonym treatment
- Stemming
- Lemmatization
- Stop words
- Parts Of Speech Tagging
- TF-IDF and its math Behind
Real-time Practicals
- Hands on- Lab using Python
CHAPTER 17: Support Vector Machine
- Understanding the SVM Concept
- Hyper plane and Kernel
- Using SVM for Regression
- Grid Search
- Model Optimizers
- Hyper parameter Tuning
Real-time Practicals
- Hands on- Lab & Model Implementation using Python
CHAPTER 18: Gradient Boosting Machine & Xgboost
- Understanding the Boosting Concept
- Hyper plane and Kernel
- Learning Rate
- Model Optimizers
- Hyper parameter Tuning
Real-time Practicals
- Hands on- Lab & Model Implementation using Python
CHAPTER 19: K MEANS CLUSTERING ALGORITHM
- Understanding Nearest Neighbors concept
- Statistics behind K Means Clustering Algorithm
Real-time Practicals
- Hands on- Lab & Model Implementation using Python
CHAPTER 20: Keras Tensor flow – MLP Deep Learning (Neural Networks)
- Understanding Deep learning
- MLP Vs other Deep Learning
- How Neural Network works & Architecture
- Activation functions.
- Model Optimizers
- Hyper parameter Tuning
- Best Practice and when to use DL
Real-time Practicals
- Hands on- Lab & Model Implementation using Python
CHAPTER 21: H20.ai
- Introduction to H20.ai
- Pros and Cons
- Available models in H20.ai
Real-time Practicals
- Hands on- Lab & Model Implementation using Python
CHAPTER 22: Sampling & Dimension Reduction (DR)
- Introduction to Sampling
- Over sampling and Under sampling
- SMOTE/SMOTENC & Near Miss
- Pros and Cons of sampling
- Introduction to DR
- PCA & it’s code
CHAPTER 23: Deployment of Model to Production
- Introduction to Pyinstaller
- Pickle and Joblib
Real-time Practicals
- Hands on- Lab & Model deployment using Python
CHAPTER 24: Tableau Basics
- Introduction to Tableau
- Data sources
- Exploratory Data Analysis
- Clustering Analysis and Inferences using Tableau
- Creating visualizations
Real-time Practicals
- Hands on- Lab using Tableau
You will be going through detailed 2 to 3 months of Data Science Hands-on training
- Detailed instructor led sessions to help you become a proficient Expert in Data Science.
- Build a Data Science professional portfolio by working on hands on assignments and projects.
- Personalized mentorship from professionals working in leading companies.
- Lifetime access to downloadable Data Science course materials, interview questions and project resources.
Credo Systemz - Velachery, Chennai
Call Us +91 9884412301
Credo Systemz - OMR, Chennai
Call Us +91 9600112302
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Data Science is a knowledge of various fields which consists of planning, methods, process and extracts the knowledge of the system or idea from the data which is in multiple formats that might be organized or unorganized like Data Mining. Data Science really very useful for managing large sets of data from the huge level of businesses which is using various algorithms and analysis. Essentially Data Science identifies the data insight. 
The Internet has an Incredible easy way to gather any kind of information. Even you can get an idea about how to design your own flight 🙂 Yes, we can get whatever we want. But the subject is how we are going to use these data efficiently? If we want to succeed, we must be adopted and updated to the latest trends and technologies. In Today’s world, everything depends on the data, from Tea shop to Multi-National companies relying upon their data. Now we understand that Data is very essential, so we have to start analyzing. The major role of Data Scientist is to analyze their company’s data and determines good tactics for their company future according to the current situation of the market. Sounds good?
- Data analytics is the heartbeat of all top organizations
- Data Science is everywhere
- You become Decision-Making person
- Data Science is rapidly increasing than expected
- Offering new revenue strategies
Know here the Skills You Should have to be a Data Scientist.
The role of a Data Scientist plays a vital role in an organization and of course it differs from company to company, the below are the list of important roles of an organization, The role of a Data Scientist plays a vital role in an organization and of course it differs from company to company, the below are the list of important roles of an organization, Assists management to make better decisions To define organizational goals and strategies Helps the staff to adopt the best practices To identity the growth opportunities Helps to spot the target audience Data Analysis and Data Cleaning To act as an statistician Assists management to make better decisions To define organizational goals and strategies Helps the staff to adopt the best practices To identity the growth opportunities Helps to spot the target audience Data Analysis and Data Cleaning To act as an statistician
The calculus of infinitesimals and linear algebra knowledge is very important for Data Science. In order to understand high-level machine learning algorithms, Mathematics skills are very essential.
In our Data Science session, we cover detailed calculus and linear algebra since it plays a very important role in data science.
In our Data Science session, we cover detailed calculus and linear algebra since it plays a very important role in data science.
Always think like a Scientist even if you are not. Statistics help you to get a clear picture of the problems. Statistics makes you to take the right techniques to solve the problems.
Our Data Science Course teaches how to prepare Statistics and how to use them. Statistics is the 1st step to become a scientist
Our Data Science Course teaches how to prepare Statistics and how to use them. Statistics is the 1st step to become a scientist
Python Training is a most commonly used programming language for various purposes like Web Apps, Games, etc., Python coming with very powerful packages that help us to easily do Data Manipulation, Visualisation, analysis, statistics, and transformation.
We cover the essentials of Python which is very much helpful for Develop, implement, and deploying programming in Data Science.
We cover the essentials of Python which is very much helpful for Develop, implement, and deploying programming in Data Science.
In our Data Science Training, we don't just deal with the data, we gonna solve data-driven problems. Also, our techniques for problem-solving should be the right ones and convince the higher authorities. They may not understand our technique since they aren't Data Scientist. So we must present and visualize the data that we collected. For the visualization & Presentation, we jump into Tableau.
As a Data Scientist, we very much depend on Tableau to express our complex data to any non-technical persons.
As a Data Scientist, we very much depend on Tableau to express our complex data to any non-technical persons.
At last and very important skill used in every part of Data Science is Deep Learning. Machine Learning separates us from Data Analyst into Data Scientist. Nowadays, Machine Learning most commonly used in all the companies like Google, Facebook, Amazon, etc.,
We cover all the common Deep Learning methods with TensorFlow and Machine Learning techniques.
Explore More about Data Science vs Machine Learning for a clear vision.
We cover all the common Deep Learning methods with TensorFlow and Machine Learning techniques.
Explore More about Data Science vs Machine Learning for a clear vision.
Harvard Business reviews calls Data Science as the sexiest job of the 21’st century, the job roles of a Data Scientist differs from one to another organization according to their domain. The below are the role of Data Scientist among companies,
- Data Scientist
- Data Architecture
- Business Analyst
- Data Engineer
- Data Analyst
- Data Administrator
- Statistician
- Data and Analytics Manager
- IBM
- Amazon
- Wipro
- Numerator
- Cloudera
- Splunk
- Microsoft
- Uber
- Apple
- Oracle
- Teradata
Data Science Combo Courses
Data Science is also called an interdisciplinary field which uses different technologies to get useful insight from the data. Hence as a Data Scientist it is very much needed to learn about different technologies related to the Data Science field, to match that we have listed down best combo packages with our Data Science course to gain the required skill set to be an successful Data Scientist.
Group Offer
If you want to avail the Best offers with Top Notch Training experience, then you landed in the right place. Credo Systemz offers high quality Software Training for affordable price, and you can also avail special additional offers if enrolled as a group. We provide special offers for various aspirants throughout the year.
“We Care for your Career growth”. If you are a group of: classmates, friends, freshers, colleagues, Professionals who are willing to learn the trending software courses, then feel free to approach the Credo Systemz career counsellor team to avail the exclusive offers.
Top Factors which makes us the Best Data Science Training Institute in Chennai
- Offering Data Science Training in Chennai on weekdays, weekends and also Data Science Online Training, fast track course, one to one training according to your requirement.
- With flexible session timings and a comfortable environment, Credo Systemz is the place to learn Best Data Science Training in Chennai
- Learn Data Science from Data Scientists who have 15+ years of professional experience, as a result, you become a skillful Data Scientist.
- In addition, during our Data Science training in Chennai, you have to analyze real-time live data and submit your report.
- We have got Maximum positive reviews across the internet which speaks about our quality training and placement.
- Moreover, Credo Systemz is the Best place to Learn Data Science training in Chennai with Real-Time ground data rather than theory Oriented.
- Importantly, Ranked as Best Data Science Training Institute in Chennai Velachery and OMR based on feedback given by our Alumni.
- Along with training, Credo Systemz stands out because of its placement team which acts as the best support system for job assistance.
- Furthermore, our Data Scientist course syllabus is highly standard and unique with "R" Programming.
- Besides training, our Data Science training in Chennai is equipped with fully hands-on and real-time data insights along with effective course content.
- Finally, you have reached the Best Data Science Training Institute in Chennai to turn Career as a Data Scientist.
Useful Data Science Resources
- Must Have Skills for a Data Scientist
- Data Scientist Salary package in India
- Data Science vs Machine Learning
