Course Design By
Nasscom & Wipro
Learn Python for Data Science: You will get a strong foundation in Python programming, starting from the basics and moving to more advanced topics like machine learning.
Prepare and Clean Data: Learn how to clean and organize messy data using Pandas and NumPy. This includes fixing missing data, normalizing values, and turning text data into numbers.
Explore Data: Understand data better by visualizing it and finding trends using tools like Matplotlib and Seaborn.
Learn Machine Learning: You will learn how to build machine learning models with Scikit-learn to predict outcomes and classify data.
Work with Advanced Techniques: You will dive into deep learning with tools like TensorFlow and Keras to build neural networks for advanced tasks.
Evaluate Your Models: Learn how to test and improve your machine learning models using cross-validation, accuracy scores, and other techniques.
Data Visualization: Create charts, graphs, and dashboards to visualize data and make your findings easy to understand for others.
Real Projects: You will apply your knowledge by working on real-world projects that simulate the challenges You will face in a data science job.
Build machine learning models that predict future outcomes.
Clean and prepare data for analysis.
Create clear data visualizations to present your findings.
Work with Pythons powerful libraries like Pandas, NumPy, and Matplotlib.
Apply statistical methods to make sense of data.
Develop real-world solutions for data problems.
Data Analyst: 50,00,000 - 66,40,000 per year
Junior Data Scientist: 58,10,000 - 74,70,000 per year
Machine Learning Engineer: 66,40,000 - 83,00,000 per year
Data Engineer: 62,25,000 - 78,85,000 per year
Move to Senior Roles: As you gain experience, you can progress into senior roles like Senior Data Scientist or Machine Learning Engineer.
Specialize in Advanced Areas: You can specialize in specific areas like deep learning or artificial intelligence (AI) for even higher-paying roles.
Start Consulting: With your skills, you could work as a freelance data consultant or even start your own data science consultancy business.
Leadership Positions: As you become an expert, you can eventually lead teams as a Chief Data Scientist or head the data science strategy for a company.
Python is Easy and Powerful: Python is simple to learn but extremely powerful for data science tasks. Its easy-to-read code and useful libraries make it an ideal language for beginners and experts alike.
High Demand in Jobs: Data science is one of the fastest-growing fields. Python is widely used by many companies, meaning there are lots of job opportunities for those with Python and data science skills.
Wide Range of Libraries: Python has many libraries that make data science tasks easier, including Pandas for data manipulation, Scikit-learn for machine learning, and TensorFlow for deep learning.
Real-World Use: Many big companies like Google, Facebook, and Amazon use Python for their data science and AI projects, which shows how valuable this skill is in the real world.
Build and train machine learning models.
Clean and prepare data for analysis.
Find insights and present them to stakeholders.
Extract, analyze, and visualize data to help make business decisions.
Use tools like Pandas and Matplotlib to explore data and present it in easy-to-understand charts.
Develop machine learning models and put them into real-time production.
Use libraries like Scikit-learn, TensorFlow, and Keras to build predictive systems.
Build and manage the systems that collect, store, and organize data.
Make sure the data is ready for analysis by data scientists.
Technology: Tech companies hire data scientists to improve products, create new features, and help make data-driven decisions.
Finance: Financial institutions use data science for things like fraud detection, analyzing market trends, and improving investment strategies.
Healthcare: In healthcare, data science helps improve patient care, optimize treatments, and analyze medical data for better results.
Retail & E-Commerce: Retailers use data science to predict demand, personalised recommendations, and optimize supply chains.
Marketing & Advertising: Data science is used to target the right customers, optimize ad campaigns, and track customer behavior.
Finance: Detecting fraud and predicting stock prices.
Healthcare: Predicting disease outbreaks or analyzing patient data.
E-Commerce: Recommending products based on customer behavior.
Social media: Analyzing trends and user sentiments.
Course materials: You will have lifetime access to recordings, lectures, and practice exercises.
Career Support: Our team helps you with resume building, job applications, and connecting with employers.
Python Libraries: Pandas, NumPy, Matplotlib, Seaborn, and Scikit-learn.
Machine Learning Tools: TensorFlow, Keras, and other tools to build AI models.
Data Handling: SQL, Excel, and data visualization tools for cleaning and presenting data.
Cloud Tools: Learn how to use cloud platforms like AWS for handling big data.
Data Visualization Project: Create various charts and graphs to visualize a dataset.
Machine Learning Project: Build a model to predict future outcomes.
Real-World Data Science Problem: Work on an actual data science problem from a business or research perspective.
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Course Design By
Nasscom & Wipro
Course Offered By
Croma Campus
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Well, Croma Campus is the only institution existing that holds thousands of candidates getting placed after acquiring training from here.
This course will hardly take your 3 months to fully get into its detailing.
It's not mandatory though, but it will be appreciable if you will belong from the computer-science background.
The training will be imparted by industry experts holding numerous years of experience in this field.
No, Python Course for Data Science is perfect for beginners. You will start from the basics and move on to more advanced topics.
The duration of this complete course is in between 1-2 months
Yes, the course includes hands-on projects that use real-world datasets so you can apply your learning.
No, Python and all the tools we use are free and open-source, so you don’t have to purchase anything extra.
There are many roles available such as Data Scientist, Data Analyst, and Machine Learning Engineer, with companies across various industries looking for skilled professionals.
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