This DSDA training has been designed keeping in mind the importance of Data Science in today’s industrial field. Through this training, anyone can master their skills in this particular domain even by starting from the very beginner’s level. From learning the very basics of python to making your very own Machine Learning prototype, this course will provide you will all the steps of climbing your way up to the competition.Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib and Seaborn, Advanced Statistical Analysis, Tableau, Machine learning with stats models and scikit-learn, Deep learning with TensorFlow. Impress interviewers by showing an understanding of Data Science field.
Starts from 26 SEPT | Saturday - 10:00 am to 1:00 pm (IST)
Starts from 30 SEPT | Wednesday - 2:00 pm to 5:00 pm (IST)
-80% discount on Marked Price.
Offer valid upto 18th of September
Learn how to pre – process data. Understand the mathematics behind Machine learning (an absolute must which other courses don’t teach!)
Start coding in Python and learn how to use it for Statistical analysis.
Perform linear and logistics regression in Python. Carry out cluster and factor analysis
Be able to create Machine learning algorithms in Python using NumPy, statsmodels and scikit-learn. Apply your skills to real - life business cases.
Use state–of–the–art Deep learning frameworks such as Google’s TensorFlow. Develop a business intuition while coding and solving tasks with big data.
Unfold the power of Deep Neural Networks. Improve Machine learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing and how hyperparameters could improve performance.
Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations.
Any student, who is enthusiastic about Data Science and Data Analytics can enroll in this training. The students are not required to have to be pro at any programming language for enrolling. Both novice and expert can take up this training. The only requisite is the attitude to learn and gain a better understanding of whatever is being taught to them.
This training will impart knowledge on an in-demand skill, in which one can pursue a career later on. With Learnbird training -
Lesson 1: Learn to program in python at a good level
Lesson 2 – Learn how to code in Jupiter Notebooks
Lesson 3 – Learn the core principles of programming
Lesson 4 – Learn how to create variables
Lesson 5 – Learn about integer, float, string and other types in Python.
Lesson 6 – Learn how to create a while loop and a for loop in Python.
Lesson 7 – Learn how to install packages in Python.
Lesson 8 – Understand the law of large numbers.
Lesson 9 – Understand the fundamentals of statistics
Lesson 10 – Learn how to work with different types of data
Lesson 11 – How to plot different types of data
Lesson 12 – Calculate the measures of central tendency, asymmetry and variability
Lesson 13 – Calculate correlation and covariance
Lesson 14 – Distinguish and work with different types of distributions
Lesson 15 – Estimate confidence intervals
Lesson 16 – Perform hypothesis testing
Lesson 17 – Make data driven decisions
Lesson 18 – Understand the mechanics of regression analysis
Lesson 19 – Carry out regression analysis
Lesson 20 – Use and understand dummy variables
Lesson 21 – Understand the concepts needed for Data Science even with Python & R
Lesson 22 – Install Tableau Desktop 2020
Lesson 23 – Connect Tableau to various Datasets: Excel and CSV files
Lesson 24 – Create Bar charts
Lesson 25 – Create Area charts
Lesson 26 – Create Maps
Lesson 27 – Create Scatterplots
Lesson 28 – Create Pie charts
Lesson 29 – Create Tree maps
Lesson 30 – Create Interactive Dashboards
Lesson 31 – Create Storylines
Lesson 32 – Understand types of joins and how they work
Lesson 33 – Work with blending data in Tableau
Lesson 34 – Create Table calculations
Lesson 35 – Work with Parameters
Lesson 36 – Create Dual Axis Charts
Lesson 37 – Create calculated fields
Lesson 38 – Create calculated fields in a blend
Lesson 39 – Export results from Tableau into PowerPoint, Word & other software
Lesson 40 – Work with Timeseries data (two methods)
Lesson 41 – Creating Data Extracts in Tableau
Lesson 42 – Understanding Aggregation, Granularity and level of detail
Lesson 43 – Adding Filters and Quick Filters
Lesson 44 – Creating Data Hierarchies
Lesson 45 – Adding Actions to Dashboards (filters & highlighting)
Lesson 46 – Assigning Geographical roles to Data Elements
Lesson 47 – Advanced Data Preparation (including latest updates in Tableau).
Candidates take up 2-week application based hands-on project to apply their learning to real-life business problems.
Our industry expert will provide all kinds of guides and assistance during the work of this project.
After completion of this training, the students are required to appear for the final examination.
Based on the results, the performers will be provided with the certifications and will eventually be eligible for Hackathon.
Students might not appear for Hackathon as it is not mandatory.
The top performers of Hackathon will be provided with the opportunity to do an internship with Learnbird Innovative Solutions © based on this domain.
Upon successful completion of the training Program, you will receive a Training Completion Certificate from Learnbird Labs in the Data Science & Data Analytics training program. This certificates will testify to your skills as an expert in data analysis.
Upon training completion, you will also receive an industry-recognized Certificate from Learnbird Innovative Solutions ©. This certificates will testify your project experience and the name of the project you have completed through this training program.
A Hackathon program will be held there after the project is completed. The top performers of Hackathon will be provided with the opportunity to do an 1 month internship with Learnbird Innovative Solutions © based on this domain. The intern will be awarded certificates and stipends based on their performance.
"Data" is the catalyst of any real world obstruction, and "analytics" is its catalyzed reaction.CEO & Founder
We have used data analytics previously to analyze student habits. It's amazing how data helps us in understanding situation by real time proof rather than just guessing along.COO & Founder
Data will be the oil for businesses in 21st century,, and Analytics will be the combustion, So Let's nurture data together, and do something big using big data as legend said "sooner is better"Data Science Expert